22140 - User contributions [en]

DiscoNet2 answers

2024-11-28T10:57:04Z

Lronn: /* Community detection / protein complex inference */

= Multiomics data integration exercise - Answers =
'''Answers written by:''' Lars Rønn Olsen

First, load the data for today's exercise:

<pre>
load("/home/projects/22140/exercise10.Rdata")
</pre>

Then, randomly pick a patient number. Let's use R to make sure it is random:

<pre>
mypt <- sample(1:10, 1)
</pre>

For that patient calculate the log2 fold change of gene expression in cancer vs normal log2(cancer expression / normal expression). Consider genes with a log2 fold change either smaller than -1 (down regulated) or larger than 1 (up regulated) dysregulated. We also consider mutated genes (with a 1 in the mutation column) as aberrated (aka nonsynonymous), so you should keep these as well. Save a list of dysregulated and/or aberrated genes.

<pre>
pt <- as.data.frame(data[[mypt]])
pt$log2fc <- log2(pt$tumor/pt$normal)
pt$gene <- rownames(pt)
seed <- rownames(pt[abs(pt$log2fc) > 1 | pt$mutation == 1,])
</pre>

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #1:'''
* What patient did you pick?
* How many genes are up or down regulated?
<pre>
table(abs(pt$log2fc) > 1)
</pre>

''Depends on your sample. Somewhere between 4 and 100.''

* Is the number of dysregulated genes what you would expect from a disease like cancer?

''Given that cancer arises from normal cells, you would expect the cancer cells to be somewhat similar to their cognate, normal cells. However, as we learned from reading the Hallmarks paper, cancer dysregulates a number of cellular functions, and for this I would probably guess between 100 and 1000 genes to be dysregulated.''

* How many genes harbor nonsynonymous mutations (Note: we only report nonsynonymous mutations in this data. Synonymous mutations have already been removed)?

''Depends on your sample. Somewhere between 1 and 32.''

* Theoretical question: Discuss the biological connection, or lack thereof, between nonsynonymous mutations and de-regulated of a) mutation and expression of the same gene and b) mutations in one gene and the expression of other genes. Use a maximum of 75 words.
For the patient sample you picked, make a node attribute table containing the following columns: “Gene”, “log2FC”, “somatic_mutations” (either 0 or 1) for ''all'' genes.

''Somatic mutations are stochastic events + selective pressure. Generally speaking, expression of a gene and its mutation status may not necessary correlate. However, in theory a loss of function mutation may activate a feedback loop increasing expression of the gene, and likewise a gain of function mutation may decrease expression resulting from feedback. Lastly, mutations of some genes may affect the expression of others. This is known as "expression quantitative trait loci"''

== Virtual pulldown ==
Load the DiscoNet package and prepare the inweb database:

<pre>
library(DiscoNet)

### Load translated database
load(file='/home/projects/22140/inweb_reduced.Rdata') # db
</pre>

Then, use the virtual_pulldown() function that you used last week, to perform a virtual pulldown with all dysregulated ''and/or'' mutated genes.

<pre>
network <- virtual_pulldown(seed_nodes = seed, database = db_reduced, id_type = "hgnc", zs_confidence_score = 0.156)
interactions <- data.frame(network$network)
node_attributes <- data.frame(network$node_attributes)
</pre>

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #2:'''
* How does a virtual pulldown work?

''It identifies proteins interacting with your input proteins, and…''

* What experiment does it simulate?

''…Simulates a complex pulldown experiment''

* What database does it query?

''The InWeb database of protein-protein interactions''

* What does the confidence score mean?

''The experimental confidence we have in the interaction''

* Is the default cutoff of 0.156 reasonable? Why/why not?

''In this context, it would appear so as we don’t get massive hairballs, nor do we get empty networks. In a real life research project, one would try multiple different thresholds and assess whether cluster member nodes share functional features to a degree where they can be considered a protein complex, or whether there a glaring outliers in terms of function, which should be filtered out''

We changed the package based on your excellent feedback last week. Now, the virtual_pulldown() function produces an interaction table (in the $network object), with confidence scores as edge attributes and a node attribute table (in the $node_attributes object) with a seed indicator and a topological score for each node.

Use the merge() function to add log2FC and mutation status to the node attribute table. Here's a hint so you don't spend too much time on this:

<pre>
node_attributes <- merge(x = node_attributes, y = pt, by.x = "nodes", by.y = "gene", all.x = TRUE)
</pre>

Make sure you understand what goes on in the function above.

Use the function graph_from_data_frame() to make an igraph object. Remember to make it undirected and add node attributes.

<pre>
g <- graph_from_data_frame(interactions, directed = FALSE, vertices = node_attributes)
</pre>

Use the relevance_filtering() function to make 3 different versions of the pulldown, with cutoffs "0", "0.5", "0.8".

<pre>
g1 <- relevance_filtering(g, 0.0)
g2 <- relevance_filtering(g, 0.5)
g3 <- relevance_filtering(g, 0.8)
</pre>

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #3:'''
* How many nodes/edges are in your three pulldown networks? (answer depends on which patient you chose, but you can find out by examining the graph objects)

''
g1
g2
g3
''
* Plot the 0.8 filtered pulldown network, colored by log2FC and mutated genes highlighted with a shape, and seed nodes highlighted in some other way. Make sure the plots added to the report are easy to read.

<pre>
ggraph(g3) +
geom_edge_link() +
geom_node_point(aes(color = log2fc, shape = as.factor(mutation)), size = 5) +
scale_color_gradient2(low = "red", mid = "white", high = "blue")
</pre>

* Does the networks look as you would expect in terms of which genes are up or down regulated or mutated? I.e. is the mutation status generally related to expression status? What would you expect?

'''For the following exercises use the network with a cutoff of 0.8'''

== Community detection / protein complex inference ==
Run the community_detection() function with the MCODE algorithm with parameters D = 0.05, haircut = TRUE, fluff = FALSE. The resulting communities may represent protein complexes that could be causative or indicative of the disease.

<pre>
communities <- community_detection(g3, algorithm = "mcode", D = 0.05, haircut = TRUE, fluff = FALSE, fdt = 0.8, loops = FALSE)
</pre>

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #4:'''
* How many nodes/edges are in your top 25 scoring communities (note: you many not have this many, in which case just report nodes/edges for all of them)

<pre>
lapply(communities[[1]], function(x) paste(vcount(x), ecount(x)))
</pre>

* How is the community score from MCODE calculate and what does it mean?

* Have a quick look [here|https://en.wikipedia.org/wiki/Protein_complex]. What do you expect a protein complex to look like? How many proteins? What clustering coefficient (how densely clustered)? Why?

''A protein complex is a group of proteins forming a quaternary structure to perform a given function. As such, one would not expect, e.g. five proteins linked together by single edges to form a long string to constitute a protein complex. Similarly, 200 proteins in a hairball probably wouldn’t be a protein complex either.''

* Based on node/edge counts alone, which of your communities could be complexes?
''Answer of course depends on your choice of patient sample, but generally you are looking networks with between 3 and 20ish nodes - pick a community that satisfies this and plot it''

<pre>
chosen_community <- 3
ggraph(communities$communities[[chosen_community]]) +
geom_edge_link() +
geom_node_point(aes(color = log2fc, shape = as.factor(mutation)), size = 5) +
geom_node_text(aes(label = name), size = 10, repel = TRUE) +
scale_color_gradient2(low = "red", mid = "white", high = "blue")
</pre>

== Gene ontology over-representation analysis ==
Now use the the fora() function from fgsea to perform an over-representation analysis on all the detected communities. Use the full list of genes from the exercise data as your background, and the biological process ontology.

<pre>
library(fgsea)
library(msigdbr)
# First, fetch gene sets
BP_df = msigdbr(species = "human", category = "C5", subcategory = "BP")
BP_list = split(x = BP_df$gene_symbol, f = BP_df$gs_name)
# repeat the analysis below with the communities you deem to be potential protein complexes
fora(pathways = BP_list, genes = V(communities$communities[[1]])$name, universe = rownames(pt))
</pre>

'''Note''': If you get a timeout error just run the function again.

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #5:'''
* Why are we asking you to use the "full list of genes" from the microarray as the background, and not ''all'' human genes? (Note that microarrays, while comprehensive, do not have probes for every single human gene).

''Because we don't know what the result would be for genes we did not measure''

* What does an over-representation test do?

''Whether certain GO terms are found at a higher frequency in a target list of genes than their frequency in background of all genes.''

* What is “over-represented” and where?

''GO terms in the target genes''

== Interpreting the results of the over-representation analysis ==
Relate functions of the significantly over-represented GO terms in each of the top 25 protein complexes to the hallmarks of cancer. Keep in mind that neither all complexes, nor all GO terms are necessarily related to cancer.

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #6:'''

* 6.1) Do any of your complexes relate to one or more of the hallmarks of cancer? How? (You will probably need to search Google here – try [GO term]+cancer or even [GO term]+”follicular thyroid cancer”).

''This depends on your sample, your clusters, and how thorough you are at checking what your GO terms mean. ''

* 6.2) If you cannot reasonably relate some of the GO terms to a cancer hallmark (and it is not unlikely that you cannot!), why do you think these non-cancer related ontologies are over-represented?

''Given that we are looking at thyroid tissue either way (healthy or sick), we expect some thyroid functions to turn up in the list.''

* 6.3) Plot the three communities you find most interesting in the context of follicular thyroid cancer. Highlight log2FC, mutation status, and seed nodes
* 6.4) How do you think these dysregulated protein complexes may drive cancer pathogenesis?
* 6.5) For the targets of your three chosen protein complexes, pick the protein best suited as a drug target and explain why based on what you have learned about network topology.

''Again, the answers to the three questions above, depends on what sample you have been working on. I chose patient 1 and a relevance score cutoff of 0.8. My community number 2 looks like this:''

[[File:Community2.png|500px]]

''Running an over-representation analysis of the complex, reveals multiple GO terms related to cell cycle and devision. Looking closer at the dysregulated genes in the complex, tells me that CDC27 might be the culprit here. I then decided to Google the gene and discovered that "CDC27 Facilitates Gastric Cancer Cell Proliferation, Invasion and Metastasis via Twist-Induced Epithelial-Mesenchymal Transition" (https://pubmed.ncbi.nlm.nih.gov/30308498/)''

''In terms of targeting, CDC27 seems like an obvious choice, since this is a small complex and all nodes have the same degree. Had the complex been larger, it could have made sense to look at the degree and betweenness centrality of the nodes as targeting hubs is a generally a good way disrupt a network''

DiscoNet2 answers

2024-11-28T10:56:40Z

Lronn: /* Multiomics data integration exercise - Answers */

= Multiomics data integration exercise - Answers =
'''Answers written by:''' Lars Rønn Olsen

First, load the data for today's exercise:

<pre>
load("/home/projects/22140/exercise10.Rdata")
</pre>

Then, randomly pick a patient number. Let's use R to make sure it is random:

<pre>
mypt <- sample(1:10, 1)
</pre>

For that patient calculate the log2 fold change of gene expression in cancer vs normal log2(cancer expression / normal expression). Consider genes with a log2 fold change either smaller than -1 (down regulated) or larger than 1 (up regulated) dysregulated. We also consider mutated genes (with a 1 in the mutation column) as aberrated (aka nonsynonymous), so you should keep these as well. Save a list of dysregulated and/or aberrated genes.

<pre>
pt <- as.data.frame(data[[mypt]])
pt$log2fc <- log2(pt$tumor/pt$normal)
pt$gene <- rownames(pt)
seed <- rownames(pt[abs(pt$log2fc) > 1 | pt$mutation == 1,])
</pre>

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #1:'''
* What patient did you pick?
* How many genes are up or down regulated?
<pre>
table(abs(pt$log2fc) > 1)
</pre>

''Depends on your sample. Somewhere between 4 and 100.''

* Is the number of dysregulated genes what you would expect from a disease like cancer?

''Given that cancer arises from normal cells, you would expect the cancer cells to be somewhat similar to their cognate, normal cells. However, as we learned from reading the Hallmarks paper, cancer dysregulates a number of cellular functions, and for this I would probably guess between 100 and 1000 genes to be dysregulated.''

* How many genes harbor nonsynonymous mutations (Note: we only report nonsynonymous mutations in this data. Synonymous mutations have already been removed)?

''Depends on your sample. Somewhere between 1 and 32.''

* Theoretical question: Discuss the biological connection, or lack thereof, between nonsynonymous mutations and de-regulated of a) mutation and expression of the same gene and b) mutations in one gene and the expression of other genes. Use a maximum of 75 words.
For the patient sample you picked, make a node attribute table containing the following columns: “Gene”, “log2FC”, “somatic_mutations” (either 0 or 1) for ''all'' genes.

''Somatic mutations are stochastic events + selective pressure. Generally speaking, expression of a gene and its mutation status may not necessary correlate. However, in theory a loss of function mutation may activate a feedback loop increasing expression of the gene, and likewise a gain of function mutation may decrease expression resulting from feedback. Lastly, mutations of some genes may affect the expression of others. This is known as "expression quantitative trait loci"''

== Virtual pulldown ==
Load the DiscoNet package and prepare the inweb database:

<pre>
library(DiscoNet)

### Load translated database
load(file='/home/projects/22140/inweb_reduced.Rdata') # db
</pre>

Then, use the virtual_pulldown() function that you used last week, to perform a virtual pulldown with all dysregulated ''and/or'' mutated genes.

<pre>
network <- virtual_pulldown(seed_nodes = seed, database = db_reduced, id_type = "hgnc", zs_confidence_score = 0.156)
interactions <- data.frame(network$network)
node_attributes <- data.frame(network$node_attributes)
</pre>

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #2:'''
* How does a virtual pulldown work?

''It identifies proteins interacting with your input proteins, and…''

* What experiment does it simulate?

''…Simulates a complex pulldown experiment''

* What database does it query?

''The InWeb database of protein-protein interactions''

* What does the confidence score mean?

''The experimental confidence we have in the interaction''

* Is the default cutoff of 0.156 reasonable? Why/why not?

''In this context, it would appear so as we don’t get massive hairballs, nor do we get empty networks. In a real life research project, one would try multiple different thresholds and assess whether cluster member nodes share functional features to a degree where they can be considered a protein complex, or whether there a glaring outliers in terms of function, which should be filtered out''

We changed the package based on your excellent feedback last week. Now, the virtual_pulldown() function produces an interaction table (in the $network object), with confidence scores as edge attributes and a node attribute table (in the $node_attributes object) with a seed indicator and a topological score for each node.

Use the merge() function to add log2FC and mutation status to the node attribute table. Here's a hint so you don't spend too much time on this:

<pre>
node_attributes <- merge(x = node_attributes, y = pt, by.x = "nodes", by.y = "gene", all.x = TRUE)
</pre>

Make sure you understand what goes on in the function above.

Use the function graph_from_data_frame() to make an igraph object. Remember to make it undirected and add node attributes.

<pre>
g <- graph_from_data_frame(interactions, directed = FALSE, vertices = node_attributes)
</pre>

Use the relevance_filtering() function to make 3 different versions of the pulldown, with cutoffs "0", "0.5", "0.8".

<pre>
g1 <- relevance_filtering(g, 0.0)
g2 <- relevance_filtering(g, 0.5)
g3 <- relevance_filtering(g, 0.8)
</pre>

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #3:'''
* How many nodes/edges are in your three pulldown networks? (answer depends on which patient you chose, but you can find out by examining the graph objects)

''
g1
g2
g3
''
* Plot the 0.8 filtered pulldown network, colored by log2FC and mutated genes highlighted with a shape, and seed nodes highlighted in some other way. Make sure the plots added to the report are easy to read.

<pre>
ggraph(g3) +
geom_edge_link() +
geom_node_point(aes(color = log2fc, shape = as.factor(mutation)), size = 5) +
scale_color_gradient2(low = "red", mid = "white", high = "blue")
</pre>

* Does the networks look as you would expect in terms of which genes are up or down regulated or mutated? I.e. is the mutation status generally related to expression status? What would you expect?

'''For the following exercises use the network with a cutoff of 0.8'''

== Community detection / protein complex inference ==
Run the community_detection() function with the MCODE algorithm with parameters D = 0.05, haircut = TRUE, fluff = FALSE. The resulting communities may represent protein complexes that could be causative or indicative of the disease.

<pre>
communities <- community_detection(g3, algorithm = "mcode", D = 0.05, haircut = TRUE, fluff = FALSE, fdt = 0.8, loops = FALSE)
</pre>

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #4:'''
* How many nodes/edges are in your top 25 scoring communities (note: you many not have this many, in which case just report nodes/edges for all of them)

<pre>
lapply(communities[[1]], function(x) paste(vcount(x), ecount(x)))
</pre>

* How is the community score from MCODE calculate and what does it mean?

* Have a quick look [here|https://en.wikipedia.org/wiki/Protein_complex]. What do you expect a protein complex to look like? How many proteins? What clustering coefficient (how densely clustered)? Why?

''A protein complex is a group of proteins forming a quaternary structure to perform a given function. As such, one would not expect, e.g. five proteins linked together by single edges to form a long string to constitute a protein complex. Similarly, 200 proteins in a hairball probably wouldn’t be a protein complex either.''

* Based on node/edge counts alone, which of your communities could be complexes?
''Answer of course depends on your choice of patient sample, but generally you are looking networks with between 3 and 20ish nodes - pick a community that satisfies this and plot it''

chosen_community <- 3

<pre>
ggraph(communities$communities[[chosen_community]]) +
geom_edge_link() +
geom_node_point(aes(color = log2fc, shape = as.factor(mutation)), size = 5) +
geom_node_text(aes(label = name), size = 10, repel = TRUE) +
scale_color_gradient2(low = "red", mid = "white", high = "blue")
</pre>

== Gene ontology over-representation analysis ==
Now use the the fora() function from fgsea to perform an over-representation analysis on all the detected communities. Use the full list of genes from the exercise data as your background, and the biological process ontology.

<pre>
library(fgsea)
library(msigdbr)
# First, fetch gene sets
BP_df = msigdbr(species = "human", category = "C5", subcategory = "BP")
BP_list = split(x = BP_df$gene_symbol, f = BP_df$gs_name)
# repeat the analysis below with the communities you deem to be potential protein complexes
fora(pathways = BP_list, genes = V(communities$communities[[1]])$name, universe = rownames(pt))
</pre>

'''Note''': If you get a timeout error just run the function again.

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #5:'''
* Why are we asking you to use the "full list of genes" from the microarray as the background, and not ''all'' human genes? (Note that microarrays, while comprehensive, do not have probes for every single human gene).

''Because we don't know what the result would be for genes we did not measure''

* What does an over-representation test do?

''Whether certain GO terms are found at a higher frequency in a target list of genes than their frequency in background of all genes.''

* What is “over-represented” and where?

''GO terms in the target genes''

== Interpreting the results of the over-representation analysis ==
Relate functions of the significantly over-represented GO terms in each of the top 25 protein complexes to the hallmarks of cancer. Keep in mind that neither all complexes, nor all GO terms are necessarily related to cancer.

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #6:'''

* 6.1) Do any of your complexes relate to one or more of the hallmarks of cancer? How? (You will probably need to search Google here – try [GO term]+cancer or even [GO term]+”follicular thyroid cancer”).

''This depends on your sample, your clusters, and how thorough you are at checking what your GO terms mean. ''

* 6.2) If you cannot reasonably relate some of the GO terms to a cancer hallmark (and it is not unlikely that you cannot!), why do you think these non-cancer related ontologies are over-represented?

''Given that we are looking at thyroid tissue either way (healthy or sick), we expect some thyroid functions to turn up in the list.''

* 6.3) Plot the three communities you find most interesting in the context of follicular thyroid cancer. Highlight log2FC, mutation status, and seed nodes
* 6.4) How do you think these dysregulated protein complexes may drive cancer pathogenesis?
* 6.5) For the targets of your three chosen protein complexes, pick the protein best suited as a drug target and explain why based on what you have learned about network topology.

''Again, the answers to the three questions above, depends on what sample you have been working on. I chose patient 1 and a relevance score cutoff of 0.8. My community number 2 looks like this:''

[[File:Community2.png|500px]]

''Running an over-representation analysis of the complex, reveals multiple GO terms related to cell cycle and devision. Looking closer at the dysregulated genes in the complex, tells me that CDC27 might be the culprit here. I then decided to Google the gene and discovered that "CDC27 Facilitates Gastric Cancer Cell Proliferation, Invasion and Metastasis via Twist-Induced Epithelial-Mesenchymal Transition" (https://pubmed.ncbi.nlm.nih.gov/30308498/)''

''In terms of targeting, CDC27 seems like an obvious choice, since this is a small complex and all nodes have the same degree. Had the complex been larger, it could have made sense to look at the degree and betweenness centrality of the nodes as targeting hubs is a generally a good way disrupt a network''

DiscoNet2 answers

2024-11-28T10:39:01Z

Lronn: /* Multiomics data integration exercise - Answers */

= Multiomics data integration exercise - Answers =
'''Answers written by:''' Lars Rønn Olsen

First, load the data for today's exercise:

<pre>
load("/home/projects/22140/exercise10.Rdata")
</pre>

Then, randomly pick a patient number. Let's use R to make sure it is random:

<pre>
mypt <- sample(1:10, 1)
</pre>

For that patient calculate the log2 fold change of gene expression in cancer vs normal log2(cancer expression / normal expression). Consider genes with a log2 fold change either smaller than -1 (down regulated) or larger than 1 (up regulated) dysregulated. We also consider mutated genes (with a 1 in the mutation column) as aberrated (aka nonsynonymous), so you should keep these as well. Save a list of dysregulated and/or aberrated genes.

<pre>
pt <- as.data.frame(data[[mypt]])
pt$log2fc <- log2(pt$tumor/pt$normal)
pt$gene <- rownames(pt)
seed <- rownames(pt[abs(pt$log2fc) > 1 | pt$mutation == 1,])
</pre>

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #1:'''
* What patient did you pick?
* How many genes are up or down regulated?
<pre>
table(pt[abs(pt$log2fc) > 1,])
</pre>

''Depends on your sample. Somewhere between 4 and 100.''

* Is the number of dysregulated genes what you would expect from a disease like cancer?

''Given that cancer arises from normal cells, you would expect the cancer cells to be somewhat similar to their cognate, normal cells. However, as we learned from reading the Hallmarks paper, cancer dysregulates a number of cellular functions, and for this I would probably guess between 100 and 1000 genes to be dysregulated.''

* How many genes harbor nonsynonymous mutations (Note: we only report nonsynonymous mutations in this data. Synonymous mutations have already been removed)?

''Depends on your sample. Somewhere between 1 and 32.''

* Theoretical question: Discuss the biological connection, or lack thereof, between nonsynonymous mutations and de-regulated of a) mutation and expression of the same gene and b) mutations in one gene and the expression of other genes. Use a maximum of 75 words.
For the patient sample you picked, make a node attribute table containing the following columns: “Gene”, “log2FC”, “somatic_mutations” (either 0 or 1) for ''all'' genes.

''Somatic mutations are stochastic events + selective pressure. Generally speaking, expression of a gene and its mutation status may not necessary correlate. However, in theory a loss of function mutation may activate a feedback loop increasing expression of the gene, and likewise a gain of function mutation may decrease expression resulting from feedback. Lastly, mutations of some genes may affect the expression of others. This is known as "expression quantitative trait loci"''

== Virtual pulldown ==
Load the DiscoNet package and prepare the inweb database:

<pre>
library(DiscoNet)

### Load translated database
load(file='/home/projects/22140/inweb.Rdata') # db
</pre>

Then, use the virtual_pulldown() function that you used last week, to perform a virtual pulldown with all dysregulated ''and/or'' mutated genes.

<pre>
network <- virtual_pulldown(seed_nodes = seed, database = db, id_type = "hgnc", zs_confidence_score = 0.156)
interactions <- data.frame(network$network)
node_attributes <- data.frame(network$node_attributes)
</pre>

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #2:'''
* How does a virtual pulldown work?

''It identifies proteins interacting with your input proteins, and…''

* What experiment does it simulate?

''…Simulates a complex pulldown experiment''

* What database does it query?

''The InWeb database of protein-protein interactions''

* What does the confidence score mean?

''The experimental confidence we have in the interaction''

* Is the default cutoff of 0.156 reasonable? Why/why not?

''In this context, it would appear so as we don’t get massive hairballs, nor do we get empty networks. In a real life research project, one would try multiple different thresholds and assess whether cluster member nodes share functional features to a degree where they can be considered a protein complex, or whether there a glaring outliers in terms of function, which should be filtered out''

We changed the package based on your excellent feedback last week. Now, the virtual_pulldown() function produces an interaction table (in the $network object), with confidence scores as edge attributes and a node attribute table (in the $node_attributes object) with a seed indicator and a topological score for each node.

Use the merge() function to add log2FC and mutation status to the node attribute table. Here's a hint so you don't spend too much time on this:

<pre>
node_attributes <- merge(x = node_attributes, y = pt, by.x = "nodes", by.y = "gene", all.x = TRUE)
</pre>

Make sure you understand what goes on in the function above.

Use the function graph_from_data_frame() to make an igraph object. Remember to make it undirected and add node attributes.

<pre>
g <- graph_from_data_frame(interactions, directed = FALSE, vertices = node_attributes)
</pre>

Use the relevance_filtering() function to make 3 different versions of the pulldown, with cutoffs "0", "0.5", "0.8".

<pre>
g1 <- relevance_filtering(g, 0.0)
g1 <- relevance_filtering(g, 0.5)
g1 <- relevance_filtering(g, 0.8)
</pre>

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #3:'''
* How many nodes/edges are in your three pulldown networks?

''1974/63033
592/18079
307/6764
''
* Plot the 0.8 filtered pulldown network, colored by log2FC and mutated genes highlighted with a shape, and seed nodes highlighted in some other way. Make sure the plots added to the report are easy to read.

<pre>
ggraph(g1) +
geom_edge_link() +
geom_node_point(aes(color = log2fc, shape = as.factor(mutation)), size = 5) +
scale_color_gradient2(low = "red", mid = "white", high = "blue")
</pre>

* Does the networks look as you would expect in terms of which genes are up or down regulated or mutated? I.e. is the mutation status generally related to expression status? What would you expect?

'''For the following exercises use the network with a cutoff of 0.8'''

== Community detection / protein complex inference ==
Run the community_detection() function with the MCODE algorithm with parameters D = 0.05, haircut = TRUE, fluff = FALSE. The resulting communities may represent protein complexes that could be causative or indicative of the disease.

<pre>
communities <- community_detection(g1, algorithm = "mcode", D = 0.05, haircut = TRUE, fluff = FALSE, fdt = 0.8, loops = FALSE)
</pre>

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #4:'''
* How many nodes/edges are in your top 25 scoring communities (note: you many not have this many, in which case just report nodes/edges for all of them)

<pre>
lapply(communities[[1]], function(x) paste(vcount(x), ecount(x)))
</pre>

* How is the community score from MCODE calculate and what does it mean?

* Have a quick look [here|https://en.wikipedia.org/wiki/Protein_complex]. What do you expect a protein complex to look like? How many proteins? What clustering coefficient (how densely clustered)? Why?

''A protein complex is a group of proteins forming a quaternary structure to perform a given function. As such, one would not expect, e.g. five proteins linked together by single edges to form a long string to constitute a protein complex. Similarly, 200 proteins in a hairball probably wouldn’t be a protein complex either.''

* Based on node/edge counts alone, which of your communities could be complexes?
''Probably all but the top one with 81 nodes and 3242 edges. Let's proceed with community 3''

<pre>
ggraph(communities$communities[[3]]) +
geom_edge_link() +
geom_node_point(aes(color = log2fc, shape = as.factor(mutation)), size = 5) +
geom_node_text(aes(label = name), size = 10, repel = TRUE) +
scale_color_gradient2(low = "red", mid = "white", high = "blue")
</pre>

== Gene ontology over-representation analysis ==
Now use the the fora() function from fgsea to perform an over-representation analysis on all the detected communities. Use the full list of genes from the exercise data as your background, and the biological process ontology.

<pre>
library(fgsea)
library(msigdbr)
# First, fetch gene sets
BP_df = msigdbr(species = "human", category = "C5", subcategory = "BP")
BP_list = split(x = BP_df$gene_symbol, f = BP_df$gs_name)
# repeat the analysis below with the communities you deem to be potential protein complexes
fora(pathways = BP_list, genes = V(communities$communities[[1]])$name, universe = rownames(pt))
</pre>

'''Note''': If you get a timeout error just run the function again.

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #5:'''
* Why are we asking you to use the "full list of genes" from the microarray as the background, and not ''all'' human genes? (Note that microarrays, while comprehensive, do not have probes for every single human gene).

''Because we don't know what the result would be for genes we did not measure''

* What does an over-representation test do?

''Whether certain GO terms are found at a higher frequency in a target list of genes than their frequency in background of all genes.''

* What is “over-represented” and where?

''GO terms in the target genes''

== Interpreting the results of the over-representation analysis ==
Relate functions of the significantly over-represented GO terms in each of the top 25 protein complexes to the hallmarks of cancer. Keep in mind that neither all complexes, nor all GO terms are necessarily related to cancer.

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #6:'''

* 6.1) Do any of your complexes relate to one or more of the hallmarks of cancer? How? (You will probably need to search Google here – try [GO term]+cancer or even [GO term]+”follicular thyroid cancer”).

''This depends on your sample, your clusters, and how thorough you are at checking what your GO terms mean. ''

* 6.2) If you cannot reasonably relate some of the GO terms to a cancer hallmark (and it is not unlikely that you cannot!), why do you think these non-cancer related ontologies are over-represented?

''Given that we are looking at thyroid tissue either way (healthy or sick), we expect some thyroid functions to turn up in the list.''

* 6.3) Plot the three communities you find most interesting in the context of follicular thyroid cancer. Highlight log2FC, mutation status, and seed nodes
* 6.4) How do you think these dysregulated protein complexes may drive cancer pathogenesis?
* 6.5) For the targets of your three chosen protein complexes, pick the protein best suited as a drug target and explain why based on what you have learned about network topology.

''Again, the answers to the three questions above, depends on what sample you have been working on. I chose patient 1 and a relevance score cutoff of 0.8. My community number 2 looks like this:''

[[File:Community2.png|500px]]

''Running an over-representation analysis of the complex, reveals multiple GO terms related to cell cycle and devision. Looking closer at the dysregulated genes in the complex, tells me that CDC27 might be the culprit here. I then decided to Google the gene and discovered that "CDC27 Facilitates Gastric Cancer Cell Proliferation, Invasion and Metastasis via Twist-Induced Epithelial-Mesenchymal Transition" (https://pubmed.ncbi.nlm.nih.gov/30308498/)''

''In terms of targeting, CDC27 seems like an obvious choice, since this is a small complex and all nodes have the same degree. Had the complex been larger, it could have made sense to look at the degree and betweenness centrality of the nodes as targeting hubs is a generally a good way disrupt a network''

DiscoNet2

2024-11-28T08:14:28Z

Lronn: /* Virtual pulldown */

= Multiomics data integration exercise =
'''Exercise written by:''' Lars Rønn Olsen

'''Learning objectives:'''
* Overall objective: learn how to extract meaningful networks from human PPI data
*# Virtual pulldowns: sampling 1st order networks and filtering "sticky proteins"
*# Finding tightly connected clusters in larger networks
*# Using the DiscoNet package in R

== Introduction ==
Today’s exercise requires the use of many of the methods you learned throughout this course. The objective is to identify aberrant, cancer-related protein complexes in follicular thyroid cancer, by analyzing gene expression and somatic mutation data from 10 patients. You will do this using the following workflow of skills you have learned in this course:
* Calculating of log2FC from healthy to cancer tissue
* Performing a virtual pulldown with the DiscoNet package
* Performing protein complex detection using MCODE
* Performing over representation analysis of GO terms using the fgsea package

== Processing data and extracting dysregulated or mutated genes ==

'''First, you need to restart your R session! "Session" -> "Restart R"!'''

First, load the data for today's exercise:

<pre>
load("/home/projects/22140/exercise10.Rdata")
</pre>

Then, randomly pick a patient number. Let's use R to make sure it is random:

<pre>
sample(1:10, 1)
</pre>

For that patient calculate the log2 fold change of gene expression in cancer vs normal log2(cancer expression / normal expression). Consider genes with a log2 fold change either smaller than -1 (down regulated) or larger than 1 (up regulated) dysregulated. We also consider mutated genes (with a 1 in the mutation column) as aberrated (aka nonsynonymous), so you should keep these as well. Save a list of dysregulated and/or aberrated genes.

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #1:'''
* What patient did you pick?
* How many genes are up or down regulated?
* Is the number of dysregulated genes what you would expect from a disease like cancer?
* How many genes harbor nonsynonymous mutations (Note: we only report nonsynonymous mutations in this data. Synonymous mutations have already been removed)?
* Theoretical question: Discuss the biological connection, or lack thereof, between nonsynonymous mutations and de-regulated of a) ''mutation and expression of the same gene'' and b) ''mutations in one gene and the expression of other genes''. Use a maximum of 75 words.

For the patient sample you picked, make a node attribute table containing the following columns: “Gene”, “log2FC”, “somatic_mutations” (either 0 or 1) for ''all'' genes.

== Virtual pulldown ==
Load the DiscoNet package and prepare the inweb database:

<pre>
library(DiscoNet)

### Load translated database
load(file='/home/projects/22140/inweb_reduced.Rdata') # db
</pre>

Then, use the virtual_pulldown() function that you used last week, to perform a virtual pulldown with all dysregulated ''and/or'' mutated genes.

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #2:'''
* How does a virtual pulldown work?
* What experiment does it simulate?
* What database does it query?
* What does the confidence score mean?
* Is the default cutoff of 0.156 reasonable? Why/why not?

We changed the package based on your excellent feedback last week. Now, the virtual_pulldown() function produces an interaction table (in the $network object), with confidence scores as edge attributes and a node attribute table (in the $node_attributes object) with a seed indicator and a topological score for each node.

Use the merge() function to add log2FC and mutation status to the node attribute table. Here's a hint so you don't spend too much time on this:

<pre>
node_attributes <- merge(x = node_attributes, y = pt, by.x = "nodes", by.y = "gene", all.x = TRUE)
</pre>

Make sure you understand what goes on in the function above.

Use the function graph_from_data_frame() to make an igraph object. Remember to make it undirected and add node attributes.

Use the relevance_filtering() function to make 3 different versions of the pulldown, with cutoffs "0", "0.5", "0.8".

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #3:'''
* How many nodes/edges are in your three pulldown networks?
* Plot the 0.8 filtered pulldown network, colored by log2FC and mutated genes highlighted with a shape, and seed nodes highlighted in some other way. Make sure the plots added to the report are easy to read.
* Does the networks look as you would expect in terms of which genes are up or down regulated or mutated? I.e. is the mutation status generally related to expression status? What would you expect?

'''For the following exercises use the network with a cutoff of 0.8'''

== Community detection / protein complex inference ==
Run the community_detection() function with the MCODE algorithm with parameters D = 0.05, haircut = TRUE, fluff = FALSE. The resulting communities may represent protein complexes that could be causative or indicative of the disease.

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #4:'''
* How many nodes/edges are in your top 25 scoring communities (note: you many not have this many, in which case just report nodes/edges for all of them)
* How is the community score from MCODE calculate and what does it mean?
* Have a quick look [here|https://en.wikipedia.org/wiki/Protein_complex]. What do you expect a protein complex to look like? How many proteins? What clustering coefficient (how densely clustered)? Why?
* Based on node/edge counts alone, which of your communities could be complexes?

== Gene ontology over-representation analysis ==
Now use the the fora() function from fgsea to perform an over-representation analysis on all the detected communities. Use the full list of genes from the exercise data as your background, and the biological process ontology.

<pre>
library(fgsea)
library(msigdbr)
# First, fetch gene sets
BP_df = msigdbr(species = "human", category = "C5", subcategory = "BP")
BP_list = split(x = BP_df$gene_symbol, f = BP_df$gs_name)
# repeat the analysis below with the communities you deem to be potential protein complexes
fora(pathways = BP_list, genes = V(communities$communities[[1]])$name, universe = rownames(pt))
</pre>

'''Note''': If you get a timeout error just run the function again.

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #5:'''
* Why are we asking you to use the "full list of genes" from the microarray as the background, and not ''all'' human genes? (Note that microarrays, while comprehensive, do not have probes for every single human gene).
* What does an over-representation test do?
* What is “over-represented” and where?

== Interpreting the results of the over-representation analysis ==
Relate functions of the significantly over-represented GO terms in each of the top 25 protein complexes to the hallmarks of cancer. Keep in mind that neither all complexes, nor all GO terms are necessarily related to cancer.

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #6:'''

* 6.1) Do any of your complexes relate to one or more of the hallmarks of cancer? How? (You will probably need to search Google here – try [GO term]+cancer or even [GO term]+”follicular thyroid cancer”).
* 6.2) If you cannot reasonably relate some of the GO terms to a cancer hallmark (and it is not unlikely that you cannot!), why do you think these non-cancer related ontologies are over-represented?
* 6.3) Plot the three communities you find most interesting in the context of follicular thyroid cancer. Highlight log2FC, mutation status, and seed nodes
* 6.4) How do you think these dysregulated protein complexes may drive cancer pathogenesis?
* 6.5) For the largets of your three chosen protein complexes, pick the protein best suited as a drug target and explain why based on what you have learned about network topology.

Heart Disease and Virtual Pulldown

2024-11-06T13:27:57Z

Lronn: /* Heart disease proteins */

= Human diseases / virtual pulldown exercise =
'''Exercise written by:''' Lars Rønn Olsen, Giorgia Moranzoni, and Rasmus Wernersson

'''Learning objectives:'''
* Overall objective: learn how to extract meaningful networks from human PPI data
*# Virtual pulldowns: sampling 1st order networks and filtering "sticky proteins"
*# Finding tightly connected clusters in larger networks
*# Using the DiscoNet package in R

== Introduction ==
[[Image:Heart+networks.png|600px|right|thumb|'''Click to zoom''' - example of the type of network characterization we aim at doing in this exercise. Seed proteins are colored yellow. (From Lage ''et al'', 2010)]]

=== The network neighborhood as an indication of function ===
As we have seen before, the function of a protein can often be inferred from the function of the proteins interacting with it. Previously we have been using this to look at the function of proteins of which little is known. Today we'll take this a step further by investigating what we can learn from the interaction partner for a '''group''' of potentially associated proteins.
=== Disease gene/protein networks ===
The basic idea is to start out with a list of genes/proteins that are known (or expected) to be involved in the same disease, even if the exact molecular basis of the disease is not understood. The hypothesis is that many of the disease-associated genes are likely to be involved in networks leading to the same phenotype (here: disease).

In the most simple case, all known disease related genes, might be part of a single network with a crystal-clear link to the disease. However, this is rarely the case.

What is more commonly the case is the situation shown in the figure to the right: the known disease related genes/protein ("seed proteins") are involved in several '''sub-networks''' describing different components of the disease.

There are several benefits from this type of analysis - most importantly:
* Identification of novel disease-related genes/proteins
* Generating hypotheses about the molecular biology behind a disease

=== Knowing where to look ===
The human interactome is HUGE. The theoretical maximum is all 20.000+ proteins interacting with each other (200 million interactions), but even the fraction we have experimental evidence for, is in the order of several hundreds of thousands of interactions between 12.000+ proteins.

As we have seen before when we looked at network properties, it will be possible to connect most nodes (here: proteins) in the network with very few steps. This is also the case with the human interactome, which taken as a whole is one giant interconnected hairball. In order to learn anything about the function of the disease genes/proteins in question, it's important to restrict what we're looking at to the '''close neighborhood''' of the proteins.

In this exercise we'll be working with two different approaches to this:
# Building a network "bottom-up" - sampling the 1st order interaction partners for a list of input proteins ("Virtual pulldowns")
# Topology based clustering on large input networks, followed by a search for cluster enriched in disease-related proteins
<br style="clear: both" />

== Exercise on "Virtual Pulldowns" ==
For this part of the exercise, we'll be using a resource created here at DTU: the "InWeb" inferred human interactome. As we have been going through in much more details in the lecture, InWeb was build by:
# Transferring interactions from model organisms to human by orthology (if a pair of interacting proteins have strong orthologs in human, the interaction is transferred)
# '''Scoring''' the reliability of the interactions. This allows for filtering out interactions with little experimental support, thus building a high-confidence network

For querying the InWeb we'll use the "DiscoNet" R package, which works as follows:

# Input: a list of protein believed to be involved in a particular biology (here: different heart diseases/developmental stages)
# For each protein, 1st order interaction partners are found
# For all input proteins and all 1st order interaction partners, a combined network is built
# For the combined network a series of '''scored subnetworks''' are build in order to filter away "sticky proteins" (as we talked about in the lecture)
# An overrepresentation analysis is performed for each complex using the fgsea package
# Finally a visual representation of the network is presented

=== Heart disease proteins ===
We'll start out with a set of proteins known to be involved in '''[https://en.wikipedia.org/wiki/Atrioventricular_septal_defect|Abnormal atrioventricular canal morphology]''' ("AACM"):

<pre>
seeds <- c("ALDH1A2", "BMP2", "CXADR", "GATA4", "HAS2", "NF1", "NKX2-5", "PITX2", "PKD2", "RXRA", "TBX1", "TBX2", "ZFPM1", "ZFPM2")
</pre>

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #1:'''
# Load the packages
<pre>
library(DiscoNet)
library(msigdbr)
library(fgsea)

The PPI database we will use is InWeb:
load(file='/home/projects/22140/inweb_reduced.Rdata')
</pre>

# Run DiscoNet with this list of proteins with the following parameters:

<pre>
network_ex2 <- virtual_pulldown(seed_nodes = seeds, database = db, id_type = "hgnc", zs_confidence_score = 0.156)
interactions <- data.frame(network_ex2$network)
node_attributes <- data.frame(network_ex2$node_attributes)
</pre>

# Convert network into igraph object with the following relevancescore cutoffs: 0, 0.5, 1

<pre>
g <- graph_from_data_frame(interactions, directed = FALSE, vertices = node_attributes)
g1 <- relevance_filtering(g, 0)
g2 <- relevance_filtering(g, 0.5)
g3 <- relevance_filtering(g, 1)
</pre>

# Look at the size of the filtered/scored networks to get an impression of how the network is narrowed down as the confidence score cut-off is raised
# How many proteins (nodes) and how many interactions (edges) are reported when a 0.2 threshold is applied? How does that compare to the full network (no cutoff)? Explain difference.

=== Visualizing networks ===

'''TASK:''' Get ready to visualize the three graphs (relevance score cutoffs 0, 0.5, 1) using ggraph.

[[Image:Office-notes-line_drawing.png|30px|left]]
'''REPORT QUESTION #2":
* Include screenshots of the networks in your report

=== Protein complex detection ===
Next up, we will use the MCODE algorithm to detect potential protein complexes using a 0.0 relevance filtering cutoff. The can be done with the "community_detection" function of DiscoNet:

<pre>
communities <- community_detection(g1, algorithm = "mcode")
</pre>

'''REPORT QUESTION #3":
Examine the resulting communities. Which one do you think may be molecular complexes and why? Paste an example of a community you believe could be a protein complex, and one you don't believe is a protein complex.

=== Functional classification ===
For the next part, we'll try to identify the function of the proteins we have found by performing Gene Ontology over-representation analysis of sub-clusters with-in the network.

This can be done with the fgsea package.

Start by loading the background gene list:

<pre>
load("/home/projects/22140/exercise9.Rdata")
</pre>

Run fora on all potential protein complexes:

<pre>
library(fgsea)
library(msigdbr)
BP_df = msigdbr(species = "human", category = "C5", subcategory = "BP")
BP_list = split(x = BP_df$gene_symbol, f = BP_df$gs_name)

fora(pathways = BP_list, genes = V(communities$communities[['COMMUNITY NUMBER']])$name, universe = all_gene_ids)
</pre>

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #4:'''
* Discuss the interpretation of the most significant results for each of the communities that could be protein complexes. Do they make biological sense in the context of heart disease?

Autumn2024

2024-11-06T09:01:34Z

Lronn: /* Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 2 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''[[media:IntroToMicroArrays 2013.pdf|A brief introduction to DNA micro-arrays]]'' - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:*[https://www.sciencedirect.com/science/article/pii/S0168952512001886?via%3Dihub|''Human diseases through the lens of network biology'']
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercises:''' [[DiscoNet|Working with "Virtual Pulldowns]] - '''Answers:''' [[DiscoNet_answers|"Virtual Pulldown" answers]]

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' Same as last week

=== Lecture 10 (November 14) - Protein isoforms 1 ===

TBA

=== Lecture 11 (November 21) - Protein isoforms 2 ===

TBA

=== Lecture 12 (November 28) - Integrating multiple omics data types for cancer research ===

:'''Lecture:''' ''Systems Biology in Cancer'' - Lars Rønn Olsen
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

TBA

= Old exam sets =

To appear on Learn

= Written exam with aids =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

DiscoNet answers

2024-11-06T08:57:54Z

Lronn: /* Human diseases / virtual pulldown exercise */

= Human diseases / virtual pulldown exercise =
'''Exercise written by:''' Lars Rønn Olsen, Giorgia Moranzoni, and Rasmus Wernersson

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #1:'''
# Load the packages
<pre>
library(DiscoNet)
library(msigdbr)
library(fgsea)

The PPI database we will use is InWeb:
load(file='/home/projects/22140/inweb_reduced.Rdata')

</pre>

# Run DiscoNet with this list of proteins with the following parameters:

<pre>
network_ex2 <- virtual_pulldown(seed_nodes = seed_nodes_ex2, database = db, id_type = "hgnc", zs_confidence_score = 0.156)
interactions <- data.frame(network_ex2$network)
node_attributes <- data.frame(network_ex2$node_attributes)
node_attributes <- merge(x = node_attributes, y = pt, by.x = "nodes", by.y = "gene", all.x = TRUE)
</pre>

# Convert network into igraph object with the following relevance score cutoffs: 0, 0.5, 1

<pre>
g <- graph_from_data_frame(interactions, directed = FALSE, vertices = node_attributes)
g1 <- relevance_filtering(g, 0)
g2 <- relevance_filtering(g, 0.5)
g3 <- relevance_filtering(g, 1)
</pre>

# Look at the size of the filtered/scored networks to get an impression of how the network is narrowed down as the confidence score cut-off is raised

''Relevance score cutoff 0 (no filtering): 452 nodes, 8806 edges''
''Relevance score cutoff 0.5: 77 nodes, 649 edges''
''Relevance score cutoff 1: 19 nodes, 11 edges''

# How many proteins (nodes) and how many interactions (edges) are reported when a 0.2 threshold is applied? How does that compare to the full network (no cutoff)? Explain difference.

''Relevance score cutoff 0.2: 242 nodes, 4766 edges''
''We observe approximately half the number of nodes and edges with a cutoff of 0.2. This means that only half the nodes had at least 20% of the edges within the network. The other half had less than that. It's unlikely that half the proteins in the unfiltered network were sticky proteins, but they probably had more to do outside the network than inside, so filtering them could be a good idea.''

=== Visualizing networks ===

'''TASK:''' Get ready to visualize the three graphs (relevance score cutoffs 0, 0.5, 1) using ggraph.

<pre>
ggraph(g1, layout = "kk") +
geom_edge_link() +
geom_node_point(size = 5)

ggraph(g2, layout = "kk") +
geom_edge_link() +
geom_node_point(size = 5)

ggraph(g3, layout = "kk") +
geom_edge_link() +
geom_node_point(size = 5)
</pre>

[[Image:Office-notes-line_drawing.png|30px|left]]
'''REPORT QUESTION #2":
* Include screenshots of the networks in your report

[[Image:G1.png|500px]]

[[Image:G2.png|500px]]

[[Image:G3.png|500px]]

=== Protein complex detection ===
Next up, we will use the MCODE algorithm to detect potential protein complexes. The can be done with the "community_detection" function of DiscoNet:

<pre>
mcode_network <- community_detection(g1, algorithm = "mcode")
</pre>

'''REPORT QUESTION #3":
Examine the resulting communities. Which one do you think may be molecular complexes and why? Paste an example of a community you believe could be a protein complex, and one you don't believe is a protein complex.

<pre>
communities <- community_detection(g1, algorithm = "mcode")
</pre>

''MCODE produces the following communities:''

<pre>
lapply(communities[[1]], function(x) paste(vcount(x), ecount(x)))

[[1]]
[1] "364 8311"

[[2]]
[1] "5 8"

[[3]]
[1] "3 3"

[[4]]
[1] "3 3"
</pre>

''Based on what we have learned, the community 1 is definitely to large to be a protein complex (protein complexes should have more than maybe 30-40 proteins, and mostly likely less than that. The rest could be good candidates, so let's visualize community 1 (bad example) and 2 (good example)''

<pre>
ggraph(communities[[1]][[1]], layout = "kk") +
geom_edge_link() +
geom_node_point(size = 5)

ggraph(communities[[1]][[2]], layout = "kk") +
geom_edge_link() +
geom_node_point(size = 5)
</pre>

''Which produces''

[[Image:Community1.png|500px]]

[[Image:Community2_w9.png|500px]]

=== Functional classification ===
For the next part, we'll try to identify the function of the proteins we have found by performing Gene Ontology over-representation analysis of sub-clusters with-in the network.

This can be done with the fgsea package.

Start by loading the background gene list:

<pre>
load("/home/projects/22140/exercise9.Rdata")
</pre>

Run fora on all potential protein complexes:

''As we saw in the previous question, community 2, 3, and 4 could be potential complexes''

<pre>
library(fgsea)
library(msigdbr)
BP_df = msigdbr(species = "human", category = "C5", subcategory = "BP")
BP_list = split(x = BP_df$gene_symbol, f = BP_df$gs_name)

head(fora(pathways = BP_list, genes = V(communities$communities[[2]])$name, universe = all_gene_ids))
head(fora(pathways = BP_list, genes = V(communities$communities[[3]])$name, universe = all_gene_ids))
head(fora(pathways = BP_list, genes = V(communities$communities[[4]])$name, universe = all_gene_ids))
</pre>

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #4:'''
* Discuss the interpretation of the most significant results for each of the communities that could be protein complexes. Do they make biological sense in the context of heart disease?

''It's immediately clear that complex 2 is involved in cardiac development:''

<pre>
1: GOBP_CARDIAC_VENTRICLE_MORPHOGENESIS 6.443594e-16 4.934504e-12
2: GOBP_CARDIAC_CHAMBER_MORPHOGENESIS 1.047694e-14 2.674414e-11
3: GOBP_CARDIAC_VENTRICLE_DEVELOPMENT 1.047694e-14 2.674414e-11
4: GOBP_CARDIAC_CHAMBER_DEVELOPMENT 4.371267e-14 8.368790e-11
5: GOBP_CELL_SURFACE_RECEPTOR_SIGNALING_PATHWAY_INVOLVED_IN_HEART_DEVELOPMENT 1.045901e-13 1.601902e-10
6: GOBP_HEART_MORPHOGENESIS 3.705408e-13 4.729336e-10
</pre>

''Same for complex 3:''

<pre>
1: GOBP_GERM_CELL_MIGRATION 0.0002322131 0.6914851 1 6
2: GOBP_CARDIAC_MUSCLE_CELL_CARDIAC_MUSCLE_CELL_ADHESION 0.0002709118 0.6914851 1 7
3: GOBP_PROTEIN_MODIFICATION_BY_SMALL_PROTEIN_CONJUGATION 0.0003764297 0.6914851 2 872
4: GOBP_AV_NODE_CELL_TO_BUNDLE_OF_HIS_CELL_SIGNALING 0.0004256966 0.6914851 1 11
5: GOBP_PROTEIN_MODIFICATION_BY_SMALL_PROTEIN_CONJUGATION_OR_REMOVAL 0.0005195136 0.6914851 2 1025
6: GOBP_AV_NODE_CELL_TO_BUNDLE_OF_HIS_CELL_COMMUNICATION 0.0005417747 0.6914851 1 14
</pre>

Heart Disease and Virtual Pulldown

2024-11-06T08:57:18Z

Lronn: /* Heart disease proteins */

= Human diseases / virtual pulldown exercise =
'''Exercise written by:''' Lars Rønn Olsen, Giorgia Moranzoni, and Rasmus Wernersson

'''Learning objectives:'''
* Overall objective: learn how to extract meaningful networks from human PPI data
*# Virtual pulldowns: sampling 1st order networks and filtering "sticky proteins"
*# Finding tightly connected clusters in larger networks
*# Using the DiscoNet package in R

== Introduction ==
[[Image:Heart+networks.png|600px|right|thumb|'''Click to zoom''' - example of the type of network characterization we aim at doing in this exercise. Seed proteins are colored yellow. (From Lage ''et al'', 2010)]]

=== The network neighborhood as an indication of function ===
As we have seen before, the function of a protein can often be inferred from the function of the proteins interacting with it. Previously we have been using this to look at the function of proteins of which little is known. Today we'll take this a step further by investigating what we can learn from the interaction partner for a '''group''' of potentially associated proteins.
=== Disease gene/protein networks ===
The basic idea is to start out with a list of genes/proteins that are known (or expected) to be involved in the same disease, even if the exact molecular basis of the disease is not understood. The hypothesis is that many of the disease-associated genes are likely to be involved in networks leading to the same phenotype (here: disease).

In the most simple case, all known disease related genes, might be part of a single network with a crystal-clear link to the disease. However, this is rarely the case.

What is more commonly the case is the situation shown in the figure to the right: the known disease related genes/protein ("seed proteins") are involved in several '''sub-networks''' describing different components of the disease.

There are several benefits from this type of analysis - most importantly:
* Identification of novel disease-related genes/proteins
* Generating hypotheses about the molecular biology behind a disease

=== Knowing where to look ===
The human interactome is HUGE. The theoretical maximum is all 20.000+ proteins interacting with each other (200 million interactions), but even the fraction we have experimental evidence for, is in the order of several hundreds of thousands of interactions between 12.000+ proteins.

As we have seen before when we looked at network properties, it will be possible to connect most nodes (here: proteins) in the network with very few steps. This is also the case with the human interactome, which taken as a whole is one giant interconnected hairball. In order to learn anything about the function of the disease genes/proteins in question, it's important to restrict what we're looking at to the '''close neighborhood''' of the proteins.

In this exercise we'll be working with two different approaches to this:
# Building a network "bottom-up" - sampling the 1st order interaction partners for a list of input proteins ("Virtual pulldowns")
# Topology based clustering on large input networks, followed by a search for cluster enriched in disease-related proteins
<br style="clear: both" />

== Exercise on "Virtual Pulldowns" ==
For this part of the exercise, we'll be using a resource created here at DTU: the "InWeb" inferred human interactome. As we have been going through in much more details in the lecture, InWeb was build by:
# Transferring interactions from model organisms to human by orthology (if a pair of interacting proteins have strong orthologs in human, the interaction is transferred)
# '''Scoring''' the reliability of the interactions. This allows for filtering out interactions with little experimental support, thus building a high-confidence network

For querying the InWeb we'll use the "DiscoNet" R package, which works as follows:

# Input: a list of protein believed to be involved in a particular biology (here: different heart diseases/developmental stages)
# For each protein, 1st order interaction partners are found
# For all input proteins and all 1st order interaction partners, a combined network is built
# For the combined network a series of '''scored subnetworks''' are build in order to filter away "sticky proteins" (as we talked about in the lecture)
# An overrepresentation analysis is performed for each complex using the fgsea package
# Finally a visual representation of the network is presented

=== Heart disease proteins ===
We'll start out with a set of proteins known to be involved in '''[https://en.wikipedia.org/wiki/Atrioventricular_septal_defect|Abnormal atrioventricular canal morphology]''' ("AACM"):

<pre>
seeds <- c("ALDH1A2", "BMP2", "CXADR", "GATA4", "HAS2", "NF1", "NKX2-5", "PITX2", "PKD2", "RXRA", "TBX1", "TBX2", "ZFPM1", "ZFPM2")
</pre>

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #1:'''
# Load the packages
<pre>
library(DiscoNet)
library(msigdbr)
library(fgsea)

The PPI database we will use is InWeb:
load(file='/home/projects/22140/inweb_reduced.Rdata')
</pre>

# Run DiscoNet with this list of proteins with the following parameters:

<pre>
network_ex2 <- virtual_pulldown(seed_nodes = seed_nodes_ex2, database = db, id_type = "hgnc", zs_confidence_score = 0.156)
interactions <- data.frame(network_ex2$network)
node_attributes <- data.frame(network_ex2$node_attributes)
</pre>

# Convert network into igraph object with the following relevancescore cutoffs: 0, 0.5, 1

<pre>
g <- graph_from_data_frame(interactions, directed = FALSE, vertices = node_attributes)
g1 <- relevance_filtering(g, 0)
g2 <- relevance_filtering(g, 0.5)
g3 <- relevance_filtering(g, 1)
</pre>

# Look at the size of the filtered/scored networks to get an impression of how the network is narrowed down as the confidence score cut-off is raised
# How many proteins (nodes) and how many interactions (edges) are reported when a 0.2 threshold is applied? How does that compare to the full network (no cutoff)? Explain difference.

=== Visualizing networks ===

'''TASK:''' Get ready to visualize the three graphs (relevance score cutoffs 0, 0.5, 1) using ggraph.

[[Image:Office-notes-line_drawing.png|30px|left]]
'''REPORT QUESTION #2":
* Include screenshots of the networks in your report

=== Protein complex detection ===
Next up, we will use the MCODE algorithm to detect potential protein complexes using a 0.0 relevance filtering cutoff. The can be done with the "community_detection" function of DiscoNet:

<pre>
communities <- community_detection(g1, algorithm = "mcode")
</pre>

'''REPORT QUESTION #3":
Examine the resulting communities. Which one do you think may be molecular complexes and why? Paste an example of a community you believe could be a protein complex, and one you don't believe is a protein complex.

=== Functional classification ===
For the next part, we'll try to identify the function of the proteins we have found by performing Gene Ontology over-representation analysis of sub-clusters with-in the network.

This can be done with the fgsea package.

Start by loading the background gene list:

<pre>
load("/home/projects/22140/exercise9.Rdata")
</pre>

Run fora on all potential protein complexes:

<pre>
library(fgsea)
library(msigdbr)
BP_df = msigdbr(species = "human", category = "C5", subcategory = "BP")
BP_list = split(x = BP_df$gene_symbol, f = BP_df$gs_name)

fora(pathways = BP_list, genes = V(communities$communities[['COMMUNITY NUMBER']])$name, universe = all_gene_ids)
</pre>

[[Image:Office-notes-line_drawing.png|30px|left]]
'''TASK/REPORT QUESTION #4:'''
* Discuss the interpretation of the most significant results for each of the communities that could be protein complexes. Do they make biological sense in the context of heart disease?

Autumn2024

2024-10-31T10:15:33Z

Lronn: /* Lecture 08 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 1 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''[[media:IntroToMicroArrays 2013.pdf|A brief introduction to DNA micro-arrays]]'' - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:*[https://www.sciencedirect.com/science/article/pii/S0168952512001886?via%3Dihub|''Human diseases through the lens of network biology'']
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercises:''' [[DiscoNet|Working with "Virtual Pulldowns]] - '''Answers:''' [[DiscoNet_answers|"Virtual Pulldown" answers]]

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 10 (November 14) - Protein isoforms 1 ===

TBA

=== Lecture 11 (November 21) - Protein isoforms 2 ===

TBA

=== Lecture 12 (November 28) - Integrating multiple omics data types for cancer research ===

:'''Lecture:''' ''Systems Biology in Cancer'' - Lars Rønn Olsen
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

TBA

= Old exam sets =

To appear on Learn

= Written exam with aids =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-10-31T10:14:38Z

Lronn: /* Lecture 08 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 1 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''[[media:IntroToMicroArrays 2013.pdf|A brief introduction to DNA micro-arrays]]'' - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:*[https://www.sciencedirect.com/science/article/pii/S0168952512001886?via%3Dihub|''Human diseases through the lens of network biology'']
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 10 (November 14) - Protein isoforms 1 ===

TBA

=== Lecture 11 (November 21) - Protein isoforms 2 ===

TBA

=== Lecture 12 (November 28) - Integrating multiple omics data types for cancer research ===

:'''Lecture:''' ''Systems Biology in Cancer'' - Lars Rønn Olsen
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

TBA

= Old exam sets =

To appear on Learn

= Written exam with aids =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-10-31T10:14:25Z

Lronn: /* Lecture 08 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 1 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''[[media:IntroToMicroArrays 2013.pdf|A brief introduction to DNA micro-arrays]]'' - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:*[[https://www.sciencedirect.com/science/article/pii/S0168952512001886?via%3Dihub|''Human diseases through the lens of network biology'']]
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 10 (November 14) - Protein isoforms 1 ===

TBA

=== Lecture 11 (November 21) - Protein isoforms 2 ===

TBA

=== Lecture 12 (November 28) - Integrating multiple omics data types for cancer research ===

:'''Lecture:''' ''Systems Biology in Cancer'' - Lars Rønn Olsen
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

TBA

= Old exam sets =

To appear on Learn

= Written exam with aids =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-10-31T10:14:02Z

Lronn: /* Lecture 08 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 1 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''[[media:IntroToMicroArrays 2013.pdf|A brief introduction to DNA micro-arrays]]'' - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:*[[''Human diseases through the lens of network biology''|https://www.sciencedirect.com/science/article/pii/S0168952512001886?via%3Dihub]]
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 10 (November 14) - Protein isoforms 1 ===

TBA

=== Lecture 11 (November 21) - Protein isoforms 2 ===

TBA

=== Lecture 12 (November 28) - Integrating multiple omics data types for cancer research ===

:'''Lecture:''' ''Systems Biology in Cancer'' - Lars Rønn Olsen
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

TBA

= Old exam sets =

To appear on Learn

= Written exam with aids =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-10-31T10:13:26Z

Lronn: /* Lecture 08 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 1 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''[[media:IntroToMicroArrays 2013.pdf|A brief introduction to DNA micro-arrays]]'' - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:* [''Human diseases through the lens of network biology''](https://www.sciencedirect.com/science/article/pii/S0168952512001886?via%3Dihub)
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 10 (November 14) - Protein isoforms 1 ===

TBA

=== Lecture 11 (November 21) - Protein isoforms 2 ===

TBA

=== Lecture 12 (November 28) - Integrating multiple omics data types for cancer research ===

:'''Lecture:''' ''Systems Biology in Cancer'' - Lars Rønn Olsen
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

TBA

= Old exam sets =

To appear on Learn

= Written exam with aids =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-10-09T10:59:46Z

Lronn: /* Lecture 06 (October 10) - Yeast Systems Biology 3 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''[[media:IntroToMicroArrays 2013.pdf|A brief introduction to DNA micro-arrays]]'' - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/27040/teachingmaterials/Furlong_Cell2012.pdf PDF])
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 10 (November 14) - Protein isoforms 1 ===

TBA

=== Lecture 11 (November 21) - Protein isoforms 2 ===

TBA

=== Lecture 12 (November 28) - Integrating multiple omics data types for cancer research ===

:'''Lecture:''' ''Systems Biology in Cancer'' - Lars Rønn Olsen
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

TBA

= Old exam sets =

To appear on Learn

= Written exam with aids =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-10-09T10:59:01Z

Lronn: /* Lecture 06 (October 10) - Yeast Systems Biology 3 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''[[file:IntroToMicroArrays 2013.pdf|A brief introduction to DNA micro-arrays]]'' - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/27040/teachingmaterials/Furlong_Cell2012.pdf PDF])
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 10 (November 14) - Protein isoforms 1 ===

TBA

=== Lecture 11 (November 21) - Protein isoforms 2 ===

TBA

=== Lecture 12 (November 28) - Integrating multiple omics data types for cancer research ===

:'''Lecture:''' ''Systems Biology in Cancer'' - Lars Rønn Olsen
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

TBA

= Old exam sets =

To appear on Learn

= Written exam with aids =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-10-09T10:58:28Z

Lronn: /* Lecture 06 (October 10) - Yeast Systems Biology 3 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''[[https://teaching.healthtech.dtu.dk/22140/images/9/94/IntroToMicroArrays_2013.pdf|A brief introduction to DNA micro-arrays]]'' - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/27040/teachingmaterials/Furlong_Cell2012.pdf PDF])
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 10 (November 14) - Protein isoforms 1 ===

TBA

=== Lecture 11 (November 21) - Protein isoforms 2 ===

TBA

=== Lecture 12 (November 28) - Integrating multiple omics data types for cancer research ===

:'''Lecture:''' ''Systems Biology in Cancer'' - Lars Rønn Olsen
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

TBA

= Old exam sets =

To appear on Learn

= Written exam with aids =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-10-09T10:57:35Z

Lronn: /* Lecture 06 (October 10) - Yeast Systems Biology 3 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' [[file:IntroToMicroArrays 2013.pdf]] - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/27040/teachingmaterials/Furlong_Cell2012.pdf PDF])
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 10 (November 14) - Protein isoforms 1 ===

TBA

=== Lecture 11 (November 21) - Protein isoforms 2 ===

TBA

=== Lecture 12 (November 28) - Integrating multiple omics data types for cancer research ===

:'''Lecture:''' ''Systems Biology in Cancer'' - Lars Rønn Olsen
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

TBA

= Old exam sets =

To appear on Learn

= Written exam with aids =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

File:IntroToMicroArrays 2013.pdf

2024-10-09T10:57:06Z

Lronn:

ExGeneOntology Yeast R answers

2024-10-03T13:24:43Z

Lronn: /* Report question #8 */

= Answers to the gene ontology exercise =
Answers by Aron Eklund, created 25 November 2014.Updated by Rasmus Wernersson, October 2020.

Here is a [[ExGeneOntology_Yeast1.5|link to the exercise]].

[[Image:Emblem-important_tiny.png‎|left]]Please remember that the web servers and their underlying data could be updated any time, so it is possible that your results may not exactly match the results listed here.

== Report question #1 ==
Q: ''How many ancestor terms are defined? With how many different types of relationships?''

By opening the page for "Cell division", and clicking on the "Graph Views" tab, one can count 2 ancestor terms (4 if the alternative visualization is used). There is only one type of relationship: is_a.

Q: ''How many children terms are defined? With how many different types of relationships?''

There are 20+ children terms. There are 5 types of relationship: is_a, part_of, negatively_regulates, positively_regulates, regulates.

== Report question #2 ==
Q: ''"Is "nucleus" a membrane-bound, or non membrane-bound organelle? On which linked GO terms do you base this conclusion?''

On the "Graph Views" tab, one sees that "nucleus" is an "intracellular membrane-bounded organelle", which in turn is a "membrane-bounded organelle". Thus, we infer that the nucleus is a '''membrane-bounded organelle'''.

Q: ''"What types of relationships are found?''

We see is_a and part_of relationships in the ancestors. If we look at the children (using the Neighborhood tab) there are many types of relationships.

== Report question #3 ==
Q: ''"Can the activities described be directed towards both DNA and RNA?''

Yes. Both DNA polymerase activity and helicase activity have child terms that are specific for DNA and RNA.

Q: ''"At which node does the "tree" branch out of the "Molecular Function" ontology and into a different ontology? With what type of relationship? Does this make biological sense?''

Looking at the "Graph Views" tab, we can see that Helicase activity doesn't branch into a different ontology. However, '''DNA Polymerase Activity''' branches into the "Biological Process" ontology (with a part_of relationship). This makes sense because catalysis of DNA polymerization is essentially a molecular event (and hence is a molecular function), and yet it is also essential for DNA biosynthesis (a biological process).

[[Image:DNA_pol_act_tree.png|thumb|center|800px|Click to zoom]]

== Report question #4 ==
Q: ''"How many (if any) cell cycle sub-phases are defined for: G1-phase, S-phase, G2-phase, and M-phase?''

If there were sub-phases, these would be listed as children with a part_of relationship. By looking at the Amigo pages for the individual mitotic phases, we can see that mitotic M phase has 4 children that are sub-phases, and that G1, G2, and S do not have sub-phases.

Q: ''"Which phases are group together into the "interphase" term?''

G1, G2, and S. (We can see these as children of "mitotic interphase")

== Report question #5 ==
Q: ''"In which meiotic cell cycle phase does synapsis happen?''

Looking at the Amigo page for synapsis, on the "Graph views" tab, one can see synapsis is part_of meiosis I.

== Report question #6 ==
Q: ''"What is the Molecular Function for POL1?''

DNA-directed DNA polymerase activity

Q: ''"How many other yeast genes are ALSO annotated to have "DNA-directed DNA polymerase activity"?''

For the ''manually annotated / curated part'': '''59''' unique genes (68 entries in the table)

== Report question #7 ==
Q: ''"Does POL1 have "Transferase Activity"? (Which GO term)''

Yes. DNA-directed DNA polymerase activity is_a (inferred) transferase activity (GO:0016740)

== Report question #8 ==
Q: ''"How many UniProt proteins are annotated with "GO:0045004 DNA replication proofreading"?''

* '''74''' (reviewed) if you search via the UniProt [https://www.uniprot.org/uniprot/?query=goa%3A%28%22DNA+replication+proofreading+%5B0045004%5D%22%29&sort=score Advanced Search interface]

Q: ''"How many of these are human?''

Three (reviewed) proteins (PolD, PolE, PolG) - is easiest found using a taxonomy filter, to only keep humun (taxid: 9606)

== Report question #9 ==
Q: ''"Population group size''

5500

Q: ''"Study group size''

16

Q: ''"Genome wide frequency of each GO term''

* DNA replication: 96 / 5500 = '''0.0175'''
* DNA repair: 259 / 5500 = '''0.0471'''
* Cell cycle: 313 / 5500 = '''0.0569'''

Q: ''"Expected number of genes annotated with each term in a random selection of yeast genes of the same size as cluster #1''

* DNA replication: 0.0175 * 16 = '''0.279'''
* DNA repair: 0.0471 * 16 = '''0.753'''
* Cell cycle: 0.0569 * 16 = '''0.911'''

Q: ''"The enrichment of observed GO terms compared to expected''

* DNA replication: 14 / 0.279 = '''50.1'''
* DNA repair: 10 / 0.753 = '''13.3'''
* Cell cycle: 8 / 0.911 = '''8.79'''

Q: ''"The p-value for each GO term''

1. First, we create a contingency table. Start by filling out the cells we already know:

{| border="1" style="border-collapse:collapse"
|+ DNA replication
|-----
! !! In study group !! Not in study group !! Total
|-----
! Has annotation
| 14 || ? || 96
|-----
! Does not have annotation
| ? || ? || ?
|-----
! Total
| 16 || ? || 5500
|}

2. Next, fill out the remaining values by arithmetic:

{| border="1" style="border-collapse:collapse"
|+ DNA replication
|-----
! !! In study group !! Not in study group !! Total
|-----
! Has annotation
| 14 || 82 || 96
|-----
! Does not have annotation
| 2 || 5402 || 5404
|-----
! Total
| 16 || 5484 || 5500
|}

3. Finally, use the 4 non-total cells to calculate a P value using Fisher's exact test. Here are two example ways to do this:

3A. In R :

<code>
<pre>
> m <- matrix(c(14, 2, 82, 5402), nrow = 2)
> m
[,1] [,2]
[1,] 14 82
[2,] 2 5402
>
> fisher.test(m)

Fisher's Exact Test for Count Data

data: m
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1
95 percent confidence interval:
102.259 4677.895
sample estimates:
odds ratio
457.4204
</pre>
</code>

3B. Using the web site we suggested ([http://graphpad.com/quickcalcs/contingency1/]), we enter the data like this:

[[File: Graphpad_pvalue_01.png| border]]

… and we get results like this:

[[File: Graphpad_pvalue_02.png| border]]

Either way, we do not get the exact P value for these data, and we must be satisfied by knowing only that it is rather small. In some cases, especially when the enrichment is less, these methods will be able to provide an exact P value.

== R exercise solutions ==

'''ASK/REPORT QUESTION #11''': Can you directly use the gene sets produced by the msigdbr function as input for the "fora" function of "fgsea"? Why/why not?

''If you read the documentation for the msigdbr and fora function you will find that msigdbr produces a data frame, while fore expects a list. You therefore need to use the split function to make the conversion (this will not be a topic on the exam, but just a reminder for you to always read the documentation of the R packages you use''

'''TASK/REPORT QUESTION #12''': Run the analysis for cluster #1 for all three GO trunks (Biological Process, Molecular Function and Cellular Component), and include top 10 significantly enriched GO terms for each ontology. Add a section to your report discussing if the results fit with what we have previously learned about the function of cluster #1.

''Depends on what clusters you picked, but generally speaking, molecular functions will be finer grained functions making up biological processes. Cellular component makes immediate sense for processes like DNA replication, which takes place in the nucleus''

<pre>
library(msigdbr)
library(fgsea)

BP_df = msigdbr(species = "S. cerevisiae", category = "C5", subcategory = "BP")
BP_list = split(x = BP_df$ensembl_gene, f = BP_df$gs_name)

MF_df = msigdbr(species = "S. cerevisiae", category = "C5", subcategory = "MF")
MF_list = split(x = MF_df$ensembl_gene, f = MF_df$gs_name)

CC_df = msigdbr(species = "S. cerevisiae", category = "C5", subcategory = "CC")
CC_list = split(x = CC_df$ensembl_gene, f = CC_df$gs_name)

load("/home/projects/22140/exercise4.Rdata")
load("/home/projects/22140/exercise5.Rdata")

target <- node_attributes[node_attributes$cluster %in% "cluster1",]$ID
BP_gsea <- fora(BP_list, target, background)
MF_gsea <- fora(MF_list, target, background)
CC_gsea <- fora(CC_list, target, background)

# A function for calculating enrichment
compute_enrichment <- function(ora, n_genes, n_universe) {
ora$relative_risk <-
(ora$overlap / ora$size) /
(n_genes / n_universe)
return(ora)
}

BP_gsea <- compute_enrichment(BP_gsea, length(target), length(background))

# Repeat as needed for the MF and CC ontologies and the other clusters

</pre>

Autumn2024

2024-10-03T12:30:05Z

Lronn: /* Block #3: Case: Human disease biology */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/27040/teachingmaterials/Furlong_Cell2012.pdf PDF])
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 10 (November 14) - Protein isoforms 1 ===

TBA

=== Lecture 11 (November 21) - Protein isoforms 2 ===

TBA

=== Lecture 12 (November 28) - Integrating multiple omics data types for cancer research ===

:'''Lecture:''' ''Systems Biology in Cancer'' - Lars Rønn Olsen
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

TBA

= Old exam sets =

To appear on Learn

= Written exam with aids =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-10-03T11:51:55Z

Lronn: /* Block #3: Case: Human disease biology */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/27040/teachingmaterials/Furlong_Cell2012.pdf PDF])
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 10 (November 14) - Integrating multiple omics data types for cancer research ===

:'''Lecture:''' ''Systems Biology in Cancer'' - Lars Rønn Olsen
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]

=== Lecture 11 (November 21) - Protein isoforms 1 ===

TBA

=== Lecture 12 (November 28) - Protein isoforms 2 ===

TBA

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

TBA

= Old exam sets =

To appear on Learn

= Written exam with aids =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-27T13:02:08Z

Lronn: /* Lecture 10 (November 14) - Systems Biology in Biomedical Research (Heart diseases) 2 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Integrating multiple omics data types for cancer research ===

:'''Lecture:''' ''Systems Biology in Cancer'' - Lars Rønn Olsen
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/27040/teachingmaterials/Furlong_Cell2012.pdf PDF])
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 10 (November 14) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 11 (November 21) - Protein isoforms 1 ===

TBA

=== Lecture 12 (November 28) - Protein isoforms 2 ===

TBA

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

TBA

= Old exam sets =

To appear on Learn

= Written exam with aids =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-26T13:42:20Z

Lronn:

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Integrating multiple omics data types for cancer research ===

:'''Lecture:''' ''Systems Biology in Cancer'' - Lars Rønn Olsen
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/27040/teachingmaterials/Furlong_Cell2012.pdf PDF])
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 10 (November 14) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Lars Rønn Olsen and Giorgia Moranzoni
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 11 (November 21) - Protein isoforms 1 ===

TBA

=== Lecture 12 (November 28) - Protein isoforms 2 ===

TBA

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

TBA

= Old exam sets =

To appear on Learn

= Written exam with aids =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-26T13:39:57Z

Lronn: /* Exam */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Integrating multiple omics data types for cancer research ===

:'''Lecture:''' ''Systems Biology in Cancer'' - Lars Rønn Olsen
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/27040/teachingmaterials/Furlong_Cell2012.pdf PDF])
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 10 (November 14) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Lars Rønn Olsen and Giorgia Moranzoni
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 11 (November 21) - Protein isoforms 1 ===

TBA

=== Lecture 12 (November 28) - Protein isoforms 2 ===

TBA

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

TBA

= Old exam sets =

To appear on Learn

= Written exam with aids =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-26T13:39:33Z

Lronn: /* Old exam sets */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Integrating multiple omics data types for cancer research ===

:'''Lecture:''' ''Systems Biology in Cancer'' - Lars Rønn Olsen
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/27040/teachingmaterials/Furlong_Cell2012.pdf PDF])
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 10 (November 14) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Lars Rønn Olsen and Giorgia Moranzoni
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 11 (November 21) - Protein isoforms 1 ===

TBA

=== Lecture 12 (November 28) - Protein isoforms 2 ===

TBA

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

TBA

= Old exam sets =

To appear on Learn

= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-26T13:39:26Z

Lronn: /* Old exam sets */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Integrating multiple omics data types for cancer research ===

:'''Lecture:''' ''Systems Biology in Cancer'' - Lars Rønn Olsen
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/27040/teachingmaterials/Furlong_Cell2012.pdf PDF])
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 10 (November 14) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Lars Rønn Olsen and Giorgia Moranzoni
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 11 (November 21) - Protein isoforms 1 ===

TBA

=== Lecture 12 (November 28) - Protein isoforms 2 ===

TBA

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

TBA

= Old exam sets =

* To appear on Learn

= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-26T13:39:05Z

Lronn: /* Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Integrating multiple omics data types for cancer research ===

:'''Lecture:''' ''Systems Biology in Cancer'' - Lars Rønn Olsen
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/27040/teachingmaterials/Furlong_Cell2012.pdf PDF])
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 10 (November 14) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Lars Rønn Olsen and Giorgia Moranzoni
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 11 (November 21) - Protein isoforms 1 ===

TBA

=== Lecture 12 (November 28) - Protein isoforms 2 ===

TBA

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

TBA

= Old exam sets =

* On Learn



--->

= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-26T13:38:44Z

Lronn: /* Lecture 08 (October 31) - Integrating multiple omics data types for cancer research */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Integrating multiple omics data types for cancer research ===

:'''Lecture:''' ''Systems Biology in Cancer'' - Lars Rønn Olsen
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/27040/teachingmaterials/Furlong_Cell2012.pdf PDF])
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 10 (November 14) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Lars Rønn Olsen and Giorgia Moranzoni
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 11 (November 21) - Protein isoforms 1 ===

TBA

=== Lecture 12 (November 28) - Protein isoforms 2 ===

TBA

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



--->

= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-26T13:38:15Z

Lronn: /* Lecture 12 (November 28) - Protein isoforms 2 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Integrating multiple omics data types for cancer research ===

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/27040/teachingmaterials/Furlong_Cell2012.pdf PDF])
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 10 (November 14) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Lars Rønn Olsen and Giorgia Moranzoni
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 11 (November 21) - Protein isoforms 1 ===

TBA

=== Lecture 12 (November 28) - Protein isoforms 2 ===

TBA

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



--->

= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-26T13:38:04Z

Lronn: /* Lecture 12 (November 28) - Dimitrios 2 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Integrating multiple omics data types for cancer research ===

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/27040/teachingmaterials/Furlong_Cell2012.pdf PDF])
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 10 (November 14) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Lars Rønn Olsen and Giorgia Moranzoni
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 11 (November 21) - Protein isoforms 1 ===

TBA

=== Lecture 12 (November 28) - Protein isoforms 2 ===

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



--->

= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-26T13:37:51Z

Lronn: /* Lecture 11 (November 21) - Protein isoforms 1 - Dimitrios Kanakoklou */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Integrating multiple omics data types for cancer research ===

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/27040/teachingmaterials/Furlong_Cell2012.pdf PDF])
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 10 (November 14) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Lars Rønn Olsen and Giorgia Moranzoni
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 11 (November 21) - Protein isoforms 1 ===

TBA

=== Lecture 12 (November 28) - Dimitrios 2 ===

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



--->

= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-26T13:37:16Z

Lronn: /* Lecture 11 (November 21) - Dimitrios 1 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Integrating multiple omics data types for cancer research ===

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/27040/teachingmaterials/Furlong_Cell2012.pdf PDF])
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 10 (November 14) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Lars Rønn Olsen and Giorgia Moranzoni
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 11 (November 21) - Protein isoforms 1 - Dimitrios Kanakoklou ===

TBA

=== Lecture 12 (November 28) - Dimitrios 2 ===

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



--->

= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-26T13:36:28Z

Lronn: /* Lecture 10 (November 14) - Systems Biology in Biomedical Research (Heart diseases) 2 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Integrating multiple omics data types for cancer research ===

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/27040/teachingmaterials/Furlong_Cell2012.pdf PDF])
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 10 (November 14) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Lars Rønn Olsen and Giorgia Moranzoni
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]

=== Lecture 11 (November 21) - Dimitrios 1 ===

=== Lecture 12 (November 28) - Dimitrios 2 ===

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



--->

= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-26T13:35:56Z

Lronn: /* Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 1 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Integrating multiple omics data types for cancer research ===

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

:'''Lecture:''' ''Systems Biology of Heart Disease'' - Rasmus Wernersson
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/27040/teachingmaterials/Furlong_Cell2012.pdf PDF])
:* Concentrate on: '''Figure 1''' and '''Box 3'''
:'''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' [[ExHumanSysbio1|Working with "Virtual Pulldowns"]] '''Answers:''' [[ExHumanSysbio1_answers|"Virtual Pulldown" answers]]

=== Lecture 10 (November 14) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

=== Lecture 11 (November 21) - Dimitrios 1 ===

=== Lecture 12 (November 28) - Dimitrios 2 ===

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



--->

= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-26T12:03:31Z

Lronn: /* Block #2: Case: Yeast systems biology */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Lars Rønn Olsen
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Integrating multiple omics data types for cancer research ===

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

=== Lecture 10 (November 14) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

=== Lecture 11 (November 21) - Dimitrios 1 ===

=== Lecture 12 (November 28) - Dimitrios 2 ===

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



--->

= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-26T12:03:15Z

Lronn: /* Block #3: Case: Human disease biology */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Kristoffer Vitting-Seerup
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----

=== Lecture 08 (October 31) - Integrating multiple omics data types for cancer research ===

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

=== Lecture 10 (November 14) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

=== Lecture 11 (November 21) - Dimitrios 1 ===

=== Lecture 12 (November 28) - Dimitrios 2 ===

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



--->

= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-26T12:02:57Z

Lronn: /* Lecture 06 (October 10) - Yeast Systems Biology 3 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Kristoffer Vitting-Seerup
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Lars Rønn Olsen
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen, Rasmus Wernersson, and Kristoffer Vitting-Seerup
----

=== Lecture 08 (October 31) - Integrating multiple omics data types for cancer research ===

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

=== Lecture 10 (November 14) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

=== Lecture 11 (November 21) - Dimitrios 1 ===

=== Lecture 12 (November 28) - Dimitrios 2 ===

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



--->

= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-26T12:02:39Z

Lronn: /* Lecture 07 (October 24) - Yeast Systems Biology 4 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Kristoffer Vitting-Seerup
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Kristoffer Vitting-Seerup
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Lars Rønn Olsen.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen, Rasmus Wernersson, and Kristoffer Vitting-Seerup
----

=== Lecture 08 (October 31) - Integrating multiple omics data types for cancer research ===

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

=== Lecture 10 (November 14) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

=== Lecture 11 (November 21) - Dimitrios 1 ===

=== Lecture 12 (November 28) - Dimitrios 2 ===

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



--->

= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-26T12:01:56Z

Lronn: /* Block #3: Case: Human disease biology */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Kristoffer Vitting-Seerup
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Kristoffer Vitting-Seerup
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Rasmus Wernersson.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen, Rasmus Wernersson, and Kristoffer Vitting-Seerup
----

=== Lecture 08 (October 31) - Integrating multiple omics data types for cancer research ===

=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 1 ===

=== Lecture 10 (November 14) - Systems Biology in Biomedical Research (Heart diseases) 2 ===

=== Lecture 11 (November 21) - Dimitrios 1 ===

=== Lecture 12 (November 28) - Dimitrios 2 ===

=== Lecture 13 (December 5) - Multiple choice test (EXAM! Participation is mandatory) + Q&A ===

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



--->

= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-26T11:50:29Z

Lronn: /* Block #3: Case: Human disease biology */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Kristoffer Vitting-Seerup
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Kristoffer Vitting-Seerup
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Rasmus Wernersson.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen, Rasmus Wernersson, and Kristoffer Vitting-Seerup
----

TBD!

=== Lecture 08 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 1 - CANCELLED ===



=== Lecture 09 (November 7) - Systems Biology in Biomedical Research (Heart diseases) 2 ===
[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Lars Rønn Olsen and Giorgia Moranzoni
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]



=== Lecture 10 (November 14) - Integrating multiple omics data types for cancer research ===
:'''Lecture:''' ''Systems Biology in Cancer'' - Kristoffer Vitting-Seerup
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]



=== Lecture 11 (November 21) - Essential R functions + exam exercise ===

:'''Lecture:''' Week 10 (and to some extent week 9) exercise walk-through
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' Old exam set (adapted to R)

<br>

=== Lecture 12 (November 28) - QnA / AMA ===

:'''Lecture:''' Kristoffer Vitting-Seerup
:'''Topics:''' Anything you would like to a refresher about

<br>

=== Lecture 13 (December 5) - Systems Biology in Biomedical Research 3 (ZS Revelen framework, drug targets) ===
:'''Lecture:''' ''Biomarker and drug target identification'' - Rasmus Wernersson.
:'''Readings:'''
:* ''Systems biology investigation of COVID-19'': ''' Network analysis of COVID19 – Intomics''' (PDF on DTU Learn)
:* It's a document with a written explanation of the COVID-19 analysis. (PDF of Intomics web-page, apologies for the sub-optimal formatting)
:* Please read all of it - ''including methods''. It is written for a non-technical audience and should be easy to understand.

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



--->

= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-26T11:43:06Z

Lronn:

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Kristoffer Vitting-Seerup
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Kristoffer Vitting-Seerup
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Rasmus Wernersson.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen, Rasmus Wernersson, and Kristoffer Vitting-Seerup
----

TBD!

=== Lecture 08 (October 24) - Systems Biology in Biomedical Research (Heart diseases) 1 - CANCELLED ===



=== Lecture 09 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 2 ===
[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Lars Rønn Olsen and Giorgia Moranzoni
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]



=== Lecture 10 (November 7) - Integrating multiple omics data types for cancer research ===
:'''Lecture:''' ''Systems Biology in Cancer'' - Kristoffer Vitting-Seerup
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]



=== Lecture 11 (November 14) - Essential R functions + exam exercise ===

:'''Lecture:''' Week 10 (and to some extent week 9) exercise walk-through
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' Old exam set (adapted to R)

<br>

=== Lecture 12 (November 21) - QnA / AMA ===

:'''Lecture:''' Kristoffer Vitting-Seerup
:'''Topics:''' Anything you would like to a refresher about

<br>

=== Lecture 13 (November 28) - Systems Biology in Biomedical Research 3 (ZS Revelen framework, drug targets) ===
:'''Lecture:''' ''Biomarker and drug target identification'' - Rasmus Wernersson.
:'''Readings:'''
:* ''Systems biology investigation of COVID-19'': ''' Network analysis of COVID19 – Intomics''' (PDF on DTU Learn)
:* It's a document with a written explanation of the COVID-19 analysis. (PDF of Intomics web-page, apologies for the sub-optimal formatting)
:* Please read all of it - ''including methods''. It is written for a non-technical audience and should be easy to understand.

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



--->

= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-26T11:42:36Z

Lronn:

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Kristoffer Vitting-Seerup
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Kristoffer Vitting-Seerup
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Rasmus Wernersson.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen, Rasmus Wernersson, and Kristoffer Vitting-Seerup
----



=== Lecture 09 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 2 ===
[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Lars Rønn Olsen and Giorgia Moranzoni
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]



=== Lecture 10 (November 7) - Integrating multiple omics data types for cancer research ===
:'''Lecture:''' ''Systems Biology in Cancer'' - Kristoffer Vitting-Seerup
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]



=== Lecture 11 (November 14) - Essential R functions + exam exercise ===

:'''Lecture:''' Week 10 (and to some extent week 9) exercise walk-through
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' Old exam set (adapted to R)

<br>

=== Lecture 12 (November 21) - QnA / AMA ===

:'''Lecture:''' Kristoffer Vitting-Seerup
:'''Topics:''' Anything you would like to a refresher about

<br>

=== Lecture 13 (November 28) - Systems Biology in Biomedical Research 3 (ZS Revelen framework, drug targets) ===
:'''Lecture:''' ''Biomarker and drug target identification'' - Rasmus Wernersson.
:'''Readings:'''
:* ''Systems biology investigation of COVID-19'': ''' Network analysis of COVID19 – Intomics''' (PDF on DTU Learn)
:* It's a document with a written explanation of the COVID-19 analysis. (PDF of Intomics web-page, apologies for the sub-optimal formatting)
:* Please read all of it - ''including methods''. It is written for a non-technical audience and should be easy to understand.

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



---->

= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-26T11:42:08Z

Lronn:

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Kristoffer Vitting-Seerup
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Kristoffer Vitting-Seerup
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Rasmus Wernersson.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen, Rasmus Wernersson, and Kristoffer Vitting-Seerup
----



=== Lecture 09 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 2 ===
[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Lars Rønn Olsen and Giorgia Moranzoni
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]



=== Lecture 10 (November 7) - Integrating multiple omics data types for cancer research ===
:'''Lecture:''' ''Systems Biology in Cancer'' - Kristoffer Vitting-Seerup
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]



=== Lecture 11 (November 14) - Essential R functions + exam exercise ===

:'''Lecture:''' Week 10 (and to some extent week 9) exercise walk-through
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' Old exam set (adapted to R)

<br>

=== Lecture 12 (November 21) - QnA / AMA ===

:'''Lecture:''' Kristoffer Vitting-Seerup
:'''Topics:''' Anything you would like to a refresher about

<br>

=== Lecture 13 (November 28) - Systems Biology in Biomedical Research 3 (ZS Revelen framework, drug targets) ===
:'''Lecture:''' ''Biomarker and drug target identification'' - Rasmus Wernersson.
:'''Readings:'''
:* ''Systems biology investigation of COVID-19'': ''' Network analysis of COVID19 – Intomics''' (PDF on DTU Learn)
:* It's a document with a written explanation of the COVID-19 analysis. (PDF of Intomics web-page, apologies for the sub-optimal formatting)
:* Please read all of it - ''including methods''. It is written for a non-technical audience and should be easy to understand.

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



--->

= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-19T12:26:47Z

Lronn: /* Lecture 07 (October 17) - Yeast Systems Biology 4 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Kristoffer Vitting-Seerup
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Kristoffer Vitting-Seerup
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 24) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Rasmus Wernersson.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen, Rasmus Wernersson, and Kristoffer Vitting-Seerup
----

=== Lecture 08 (October 24) - Systems Biology in Biomedical Research (Heart diseases) 1 - CANCELLED ===



=== Lecture 09 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 2 ===
[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Lars Rønn Olsen and Giorgia Moranzoni
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]



=== Lecture 10 (November 7) - Integrating multiple omics data types for cancer research ===
:'''Lecture:''' ''Systems Biology in Cancer'' - Kristoffer Vitting-Seerup
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]



=== Lecture 11 (November 14) - Essential R functions + exam exercise ===

:'''Lecture:''' Week 10 (and to some extent week 9) exercise walk-through
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' Old exam set (adapted to R)

<br>

=== Lecture 12 (November 21) - QnA / AMA ===

:'''Lecture:''' Kristoffer Vitting-Seerup
:'''Topics:''' Anything you would like to a refresher about

<br>

=== Lecture 13 (November 28) - Systems Biology in Biomedical Research 3 (ZS Revelen framework, drug targets) ===
:'''Lecture:''' ''Biomarker and drug target identification'' - Rasmus Wernersson.
:'''Readings:'''
:* ''Systems biology investigation of COVID-19'': ''' Network analysis of COVID19 – Intomics''' (PDF on DTU Learn)
:* It's a document with a written explanation of the COVID-19 analysis. (PDF of Intomics web-page, apologies for the sub-optimal formatting)
:* Please read all of it - ''including methods''. It is written for a non-technical audience and should be easy to understand.

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-19T12:26:19Z

Lronn: /* Lecture 07 (October 12) - Yeast Systems Biology 4 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Kristoffer Vitting-Seerup
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Kristoffer Vitting-Seerup
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 17) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Rasmus Wernersson.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen, Rasmus Wernersson, and Kristoffer Vitting-Seerup
----

=== Lecture 08 (October 24) - Systems Biology in Biomedical Research (Heart diseases) 1 - CANCELLED ===



=== Lecture 09 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 2 ===
[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Lars Rønn Olsen and Giorgia Moranzoni
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]



=== Lecture 10 (November 7) - Integrating multiple omics data types for cancer research ===
:'''Lecture:''' ''Systems Biology in Cancer'' - Kristoffer Vitting-Seerup
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]



=== Lecture 11 (November 14) - Essential R functions + exam exercise ===

:'''Lecture:''' Week 10 (and to some extent week 9) exercise walk-through
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' Old exam set (adapted to R)

<br>

=== Lecture 12 (November 21) - QnA / AMA ===

:'''Lecture:''' Kristoffer Vitting-Seerup
:'''Topics:''' Anything you would like to a refresher about

<br>

=== Lecture 13 (November 28) - Systems Biology in Biomedical Research 3 (ZS Revelen framework, drug targets) ===
:'''Lecture:''' ''Biomarker and drug target identification'' - Rasmus Wernersson.
:'''Readings:'''
:* ''Systems biology investigation of COVID-19'': ''' Network analysis of COVID19 – Intomics''' (PDF on DTU Learn)
:* It's a document with a written explanation of the COVID-19 analysis. (PDF of Intomics web-page, apologies for the sub-optimal formatting)
:* Please read all of it - ''including methods''. It is written for a non-technical audience and should be easy to understand.

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-19T09:52:49Z

Lronn: /* Lecture 03 (September 19) - Intro 3 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to network topology exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Kristoffer Vitting-Seerup
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Kristoffer Vitting-Seerup
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 12) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Rasmus Wernersson.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen, Rasmus Wernersson, and Kristoffer Vitting-Seerup
----

=== Lecture 08 (October 24) - Systems Biology in Biomedical Research (Heart diseases) 1 - CANCELLED ===



=== Lecture 09 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 2 ===
[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Lars Rønn Olsen and Giorgia Moranzoni
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]



=== Lecture 10 (November 7) - Integrating multiple omics data types for cancer research ===
:'''Lecture:''' ''Systems Biology in Cancer'' - Kristoffer Vitting-Seerup
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]



=== Lecture 11 (November 14) - Essential R functions + exam exercise ===

:'''Lecture:''' Week 10 (and to some extent week 9) exercise walk-through
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' Old exam set (adapted to R)

<br>

=== Lecture 12 (November 21) - QnA / AMA ===

:'''Lecture:''' Kristoffer Vitting-Seerup
:'''Topics:''' Anything you would like to a refresher about

<br>

=== Lecture 13 (November 28) - Systems Biology in Biomedical Research 3 (ZS Revelen framework, drug targets) ===
:'''Lecture:''' ''Biomarker and drug target identification'' - Rasmus Wernersson.
:'''Readings:'''
:* ''Systems biology investigation of COVID-19'': ''' Network analysis of COVID19 – Intomics''' (PDF on DTU Learn)
:* It's a document with a written explanation of the COVID-19 analysis. (PDF of Intomics web-page, apologies for the sub-optimal formatting)
:* Please read all of it - ''including methods''. It is written for a non-technical audience and should be easy to understand.

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-11T13:35:44Z

Lronn: /* Lecture 02 (September 12) - Intro 2 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to igraph exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Kristoffer Vitting-Seerup
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Kristoffer Vitting-Seerup
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 12) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Rasmus Wernersson.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen, Rasmus Wernersson, and Kristoffer Vitting-Seerup
----

=== Lecture 08 (October 24) - Systems Biology in Biomedical Research (Heart diseases) 1 - CANCELLED ===



=== Lecture 09 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 2 ===
[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Lars Rønn Olsen and Giorgia Moranzoni
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]



=== Lecture 10 (November 7) - Integrating multiple omics data types for cancer research ===
:'''Lecture:''' ''Systems Biology in Cancer'' - Kristoffer Vitting-Seerup
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]



=== Lecture 11 (November 14) - Essential R functions + exam exercise ===

:'''Lecture:''' Week 10 (and to some extent week 9) exercise walk-through
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' Old exam set (adapted to R)

<br>

=== Lecture 12 (November 21) - QnA / AMA ===

:'''Lecture:''' Kristoffer Vitting-Seerup
:'''Topics:''' Anything you would like to a refresher about

<br>

=== Lecture 13 (November 28) - Systems Biology in Biomedical Research 3 (ZS Revelen framework, drug targets) ===
:'''Lecture:''' ''Biomarker and drug target identification'' - Rasmus Wernersson.
:'''Readings:'''
:* ''Systems biology investigation of COVID-19'': ''' Network analysis of COVID19 – Intomics''' (PDF on DTU Learn)
:* It's a document with a written explanation of the COVID-19 analysis. (PDF of Intomics web-page, apologies for the sub-optimal formatting)
:* Please read all of it - ''including methods''. It is written for a non-technical audience and should be easy to understand.

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-11T13:35:31Z

Lronn: /* Lecture 02 (September 12) - Intro 2 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] '''Answers''': [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|Handout answers]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to igraph exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Kristoffer Vitting-Seerup
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Kristoffer Vitting-Seerup
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 12) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Rasmus Wernersson.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen, Rasmus Wernersson, and Kristoffer Vitting-Seerup
----

=== Lecture 08 (October 24) - Systems Biology in Biomedical Research (Heart diseases) 1 - CANCELLED ===



=== Lecture 09 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 2 ===
[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Lars Rønn Olsen and Giorgia Moranzoni
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]



=== Lecture 10 (November 7) - Integrating multiple omics data types for cancer research ===
:'''Lecture:''' ''Systems Biology in Cancer'' - Kristoffer Vitting-Seerup
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]



=== Lecture 11 (November 14) - Essential R functions + exam exercise ===

:'''Lecture:''' Week 10 (and to some extent week 9) exercise walk-through
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' Old exam set (adapted to R)

<br>

=== Lecture 12 (November 21) - QnA / AMA ===

:'''Lecture:''' Kristoffer Vitting-Seerup
:'''Topics:''' Anything you would like to a refresher about

<br>

=== Lecture 13 (November 28) - Systems Biology in Biomedical Research 3 (ZS Revelen framework, drug targets) ===
:'''Lecture:''' ''Biomarker and drug target identification'' - Rasmus Wernersson.
:'''Readings:'''
:* ''Systems biology investigation of COVID-19'': ''' Network analysis of COVID19 – Intomics''' (PDF on DTU Learn)
:* It's a document with a written explanation of the COVID-19 analysis. (PDF of Intomics web-page, apologies for the sub-optimal formatting)
:* Please read all of it - ''including methods''. It is written for a non-technical audience and should be easy to understand.

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

Autumn2024

2024-09-11T13:34:49Z

Lronn: /* Lecture 02 (September 12) - Intro 2 */

= Course 22140 - plan for autumn 2024 =

'''Teachers:'''
* Lars Rønn Olsen (course organizer) - '''contact:''' [mailto:lronn@dtu.dk lronn@dtu.dk]
* Kristoffer Vitting-Seerup (course organizer) - '''contact:''' [mailto:krivi@dtu.dk krivi@dtu.dk]
* Rasmus Wernersson (external lecturer) - '''contact:''' [mailto:rawe@dtu.dk rawe@dtu.dk]
* Dimitrios Kanakoglou (teaching assistant) - '''contact:''' [mailto:dimkan@dtu.dk dimkan@dtu.dk]



= DTU Learn =
* Link: [https://learn.inside.dtu.dk/d2l/home/216012 Course 22140, Autumn 2024 @ DTU Learn]
* Link: [https://learn.inside.dtu.dk/d2l/home/216053 Course 22150, Autumn 2024 @ DTU Learn]
<br>

= Bioinformatics =
Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.
* [https://teaching.healthtech.dtu.dk/22111/ Course 22111] - ''Introduction to Bioinformatics''
* [[Exercise:_The_protein_database_UniProt|UniProt exercise]] ([[ExUniProt-answers|answers]]) - This is an important one, as we use UniProt a lot in this course.
<br>

= R =
For the computer exercises we will be using R to process data, analyze, and visualize the biological networks. R is Open Source and freely available for Windows, Mac and Linux. We will be utilizing a RStudio server cloud solution to make sure that everyone uses the same version of R and the needed packages. You can log in with your DTU credentials [https://teaching.healthtech.dtu.dk/22140/rstudio.php here].

'''NOTE''': In order to produce plots with RStudio server, you need to have the appropriate graphics device activated. If you have X11 installed, this should work without any further actions. If you do not, you will get an error whenever you try to plot anything. To mitigate this, open Rstudio server, go to "Tools" (options bar at the top of the screen), select "Global options" from the drop down menu, select the "Graphics" tab, and change "Backend" to "Cairo".
<br><br>

= Weekly assignments =
[[Image:Office-notes-line_drawing.png|40px|left]]
As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

Following the exercise the reports will be handed in using the peer grade system. We will assign your report to three co-students to provide you with feedback.

'''Important:''' The reports are not as such mandatory, but it is HIGHLY recommended to turn them in, as this is excellent training for the exam.

'''Allowed formats:'''
# Plain text + figures as extra files
# Microsoft Word (*.doc, *.docx)
# PDF: use ANY word-processing software you like (e.g. "Pages") and save/print the result to a PDF.

= Lecture plan, autumn 2024 =

== When and Where ==
* '''When:''' Each '''Thursday''' from '''13:00-17:00'''
* '''Where:''' Building '''303A''' auditorium/group-room '''045'''
<hr>

== Block #1: Introduction ==
'''Responsible for this block:''' Lars Rønn Olsen and Rasmus Wernersson
----
=== Lecture 01 (September 5) - Intro 1 ===

:'''Lecture:''' ''Introduction to Systems Biology and biological networks'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:''' ''Can a Biologist fix a radio?'' - Lazebnik Y., Cancer Cell 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W01_Lazebnik_CancerCell2002.pdf PDF])
:'''Exercise:''' [[igraphIntro_Ex_v1|Introduction to working with networks in R]] - '''Answers:''' [[igraphIntro_Answers_v1|Exercise #1 answers]]

=== Lecture 02 (September 12) - Intro 2 ===

:'''Lecture:''' ''Protein-protein interaction networks. Experimental methods and interpretation.'' - Lars Rønn Olsen

:'''Slides:''' To appear on DTU Learn
:'''Hand-outs:''' ''SnapShot: Protein-Protein Interaction Networks'' - Seebacher & Gavin, Nature 2011 ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - focus on the EXPERIMENTAL METHODS part for this week.
:'''Readings:'''
<blockquote>
* Lecture note on ''quality scoring of protein-protein interaction data, notes and examples'' ([https://teaching.healthtech.dtu.dk/material/22140/W02_scoring_of_PPI.pdf PDF])
* ''Comparative assessment of large-scale data sets of protein-protein interactions'' - von Mering C, ''et al''. Nature 2002 ([https://teaching.healthtech.dtu.dk/material/22140/W02_Comparative_assessment_of_large-scale_data_sets_of_protein-protein.pdf PDF])
</blockquote>

:'''Exercise:'''
:* [[Media:W02_exercises_v7_corrected.pdf|Building protein-protein interaction networks from experimental data]] - [[Media:W02_exercises_with_answers_2021_CORRECTED.pdf|solutions]]
:* [[Media:Exercise_help_sheet.pdf|Note taking sheet for help with ex. 5,7,8,9]] - Consider printing this for taking notes
:* [[Ex_handouts_igraph|Visualization of the networks from the hand-out exercise]] - '''Answers''': [[Ex_handouts_igraph_solution|Exercise #2 answers]]

=== Lecture 03 (September 19) - Intro 3 ===

:'''Lecture:''' ''Network topology'' - Lars Rønn Olsen
:'''Slides:''' On DTU Learn.

:'''Hand-outs:''' SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) ([https://teaching.healthtech.dtu.dk/material/22140/SnapShot_Cell2011.pdf PDF]) - read the rest for this week.
:'''Readings:''' Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 ([https://teaching.healthtech.dtu.dk/material/22140/W03_Barabasi_Oltvai_NatRevGen2004.pdf PDF]) - concentrate on '''Box 1''' and '''Box 2'''.

:'''Exercises:'''
<blockquote>
#'''Handout exercise:''' Network topology exercise ([https://teaching.healthtech.dtu.dk/material/22140/W03_Network_topology_exercise_v3.pdf PDF])
#'''Computer exercise:''' Topology/statistics/modules [[ExTopology1_igraph|Network topology and statistics]] - '''Answers''': [[ExTopology1_igraph_solutions|Answers to igraph exercise]]
</blockquote>

== Block #2: Case: Yeast systems biology ==
'''Responsible for this block:''' Rasmus Wernersson and Kristoffer Vitting-Seerup
----

=== Lecture 04 (September 26) - Yeast Systems Biology 1 ===

:'''Lecture:''' ''Yeast Cell Cycle introduction'' - Rasmus Wernersson.
:'''Slides:''' Will be uploaded to DTU Learn
:'''Readings:'''
:* Background on budding yeast cell cycle and cell cycle regulation ([https://teaching.healthtech.dtu.dk/material/22140/Budding_Yeast_Cell_Cycle_Model.pdf PDF]).
:* Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
:* '''Important:''' You don't need to understand all the finer points about the regulation, but make sure you known the '''phases''' of the cell cycle.

:'''Saccharomyces Genome Database:''' http://www.yeastgenome.org/
:'''Exercise:''' [[ExYeastSysBio_R|Yeast cell cycle 1 - introduction to data and methods]] - '''Answers:''' [[ExYeastSysBio_R_answers|Yeast 1 answers]]

=== Lecture 05 (October 3) - Yeast Systems Biology 2 ===

:'''Lecture:''' ''Gene Ontology and large scale data analysis'' - Rasmus Wernersson
:'''Readings:''' Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
:* Intro for bioinformaticians: '''The what, where, how and why of gene ontology - a primer for bioinformaticians''' - [https://teaching.healthtech.dtu.dk/material/22140/Bbr002.pdf PDF] (NEW LINK) (focus on the first three pages).
:**Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
:* Intro for biologists: '''Gene Ontology: tool for the uniﬁcation of biology''' - [https://teaching.healthtech.dtu.dk/material/22140/GO_NATURE_GENETICS_2000.pdf PDF] (NEW LINK)
:**Describes more the general idea behind GO and why it is useful.
:'''Slides:''' On DTU Learn

:'''Exercise:''' [[ExGeneOntology_Yeast_R|Gene Ontology - yeast cell cycle examples]] - '''Answers:''' [[ExGeneOntology_Yeast_R_answers|answers]]

=== Lecture 06 (October 10) - Yeast Systems Biology 3 ===

:'''Lecture:''' ''Introduction to transcriptomics'' - Kristoffer Vitting-Seerup
:'''Readings:''' ''A brief introduction to DNA micro-arrays'' ([https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/691406/View DTU Learn]) - Rasmus Wernersson
:'''Background:''' (Optional) - If you need a reminder about how the Log2 function works, then have a look at '''Appendix A''' in Thomas Schneider's '' Information Theory Primer'' ([https://teaching.healthtech.dtu.dk/material/22140/informationtheory_primer.pdf PDF])
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics_R|Yeast cell cycle: single point arrest DNA microarray studies]] - '''Answers:''' [[ExYeastCellCycle_answers|Answers]]

=== Lecture 07 (October 12) - Yeast Systems Biology 4 ===

:'''Lecture:''' ''How proteins collaborate during the phases of cell devision'' - Rasmus Wernersson.
:'''Readings:''' [https://teaching.healthtech.dtu.dk/material/22140/Cyclebase1_2008.pdf PDF Cyclebase paper] - (skim it - make sure to understand '''Fig 1''').
:'''Slides:''' To appear on DTU Learn

:'''Exercise:''' [[ExYeastCellCycleTranscriptomics2_R|Mapping temporal expression data onto networks]] '''Answers:''' [[ExYeastCellCycleTranscriptomics2_R_answers|answers]]

<hr>
<div align="center">
'''Autumn vacation'''
(Week 42)
</div>
<hr>

== Block #3: Case: Human disease biology ==
'''Responsible for this block:''' Lars Rønn Olsen, Rasmus Wernersson, and Kristoffer Vitting-Seerup
----

=== Lecture 08 (October 24) - Systems Biology in Biomedical Research (Heart diseases) 1 - CANCELLED ===



=== Lecture 09 (October 31) - Systems Biology in Biomedical Research (Heart diseases) 2 ===
[[Image:XKCD_significant.png|80px|thumb|right]]
:'''Lecture:''' ''Virtual pulldown and protein complex detection'' - Lars Rønn Olsen and Giorgia Moranzoni
:'''Readings:'''
:* ''Human diseases through the lens of network biology'' ([https://teaching.healthtech.dtu.dk/material/22140/Furlong_Cell2012.pdf PDF]) - Concentrate on: '''Figure 1''' and '''Box 3'''
:* '''Heart development video:''' https://www.youtube.com/watch?v=5DIUk9IXUaI
:'''Extra:''' (not curriculum)
:* The heart disease paper: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913399/
:* The MCODE paper: http://www.biomedcentral.com/1471-2105/4/2
:'''Exercises:''' [[DiscoNet|DiscoNet]] - '''Answers:''' [[DiscoNet_answers|DiscoNet answers]]



=== Lecture 10 (November 7) - Integrating multiple omics data types for cancer research ===
:'''Lecture:''' ''Systems Biology in Cancer'' - Kristoffer Vitting-Seerup
:'''Readings:'''
:* ''The Hallmarks of Cancer'', Hanahan & Weinberg 2011 ([https://www.cell.com/fulltext/S0092-8674(11)00127-9 Article link])
:'''Slides:''' [https://learn.inside.dtu.dk/d2l/le/content/167355/viewContent/704041/View On DTU Learn]
:'''Exercises:''' [[DiscoNet2|Multiomics data integration]] '''Answers:''' [[DiscoNet2_answers|answers]]



=== Lecture 11 (November 14) - Essential R functions + exam exercise ===

:'''Lecture:''' Week 10 (and to some extent week 9) exercise walk-through
:'''Slides:''' To appear on DTU Learn
:'''Exercise:''' Old exam set (adapted to R)

<br>

=== Lecture 12 (November 21) - QnA / AMA ===

:'''Lecture:''' Kristoffer Vitting-Seerup
:'''Topics:''' Anything you would like to a refresher about

<br>

=== Lecture 13 (November 28) - Systems Biology in Biomedical Research 3 (ZS Revelen framework, drug targets) ===
:'''Lecture:''' ''Biomarker and drug target identification'' - Rasmus Wernersson.
:'''Readings:'''
:* ''Systems biology investigation of COVID-19'': ''' Network analysis of COVID19 – Intomics''' (PDF on DTU Learn)
:* It's a document with a written explanation of the COVID-19 analysis. (PDF of Intomics web-page, apologies for the sub-optimal formatting)
:* Please read all of it - ''including methods''. It is written for a non-technical audience and should be easy to understand.

:'''Slides:''' To appear on DTU Learn
:'''Exercise:'''
:* PDF on Learn
:'''Link to ZS Revelen:''' '''https://zs-revelen.com/'''
:*'''Please register''' your email with ZS Revelen before the exercise. '''Please use your DTU email.'''
<br>

= Old exam sets =

* On Learn



= Exam =
* '''Date: 9/12 2024
* '''Time: (will be) available via https://eksamensplan.dtu.dk/
* '''Where: (will be) available via https://eksamensplan.dtu.dk/

File:W02 exercises with answers 2021 CORRECTED.pdf

2024-09-11T13:33:34Z

Lronn: