Bcell Epitope prediction

2025-10-24T11:25:13Z

Carol: Created page with "We want to look for epitopes on the HIV GP120 protein. We will use both sequence-based and structure-based methods. Input data. Go to the pdb homepage and look for the pdb entry 4LSP. It is GP120 complexed with a broadly neutralizing antibody. These antibodies are extremely powerful, since they are effective against many different strains. Q1: Download both the structure (pdb) and the sequence (fasta) of the proteins in this entry. Which proteins are in chain G, L and..."

We want to look for epitopes on the HIV GP120 protein. We will use both sequence-based and structure-based methods.
Input data.

Go to the pdb homepage and look for the pdb entry 4LSP. It is GP120 complexed with a broadly neutralizing antibody. These antibodies are extremely powerful, since they are effective against many different strains.

Q1: Download both the structure (pdb) and the sequence (fasta) of the proteins in this entry. Which proteins are in chain G, L and H respectively?

hint: you can find this information in the structure web-page, in the PDB file itself (you can open it with a text editor), and, if you are more experienced, in the fasta file.

Q2: using pymol, can you identify which residues are part of the epitope? Is the epitope linear? Does it have a linear core?

Hints: remove the waters, then select the antibody and modify this selection to find residues in a 5Å sphere. You can find a quick video on how to do this in the hands-on prerequisites.

Q3: using pymol, identify the antibody in the structure, select and remove it (action -> remove atoms). Save the resulting molecule as antigen.pdb

You can save using the GUI (remember to select PDB as option) as well as typing "save antigen.pdb" in the command line

Now we are starting with a sequence-based prediction of the epitopes.

Bepipred 2/3

Go to the bepipred website and upload the sequence of GP120. Leave the default parameters and submit the job. Don't close the window because we will need it again!

Q4: does the Bepipred prediction overlap with the actual epitope?

Be careful: pdb file numbering does not always start from 1! Compare the numbering of the pdb with the one returned by Bepipred.

Repeat the prediction now using BepiPred3.

Q5: Does the prediction overlap with our epitope now?

Q6: What is different in BepiPred 2 compared to Bepipred 3?
Discotope 2/3

Finally, let's use DTU Discotope server.
Load the antigen.pdb file and submit the prediction. Save the output as discotope.pdb
Once again, the prediction is in the b-factor field (but you can download it in other formats as well)
Load it in pymol and colour according to the b-factor.

Q7: Does the prediction overlap with our epitope?

Q8: Which prediction best matches our epitope?

Q9: Use Discotope to predict the epitopes in the simian HIV GP120 homolog (pdb code 3FUS). If you want to save time, use this pre-cleaned PDB. Compare the results. Try and explain the differences. According to you is it a meaningful result or not? Please note that some bugs might occur, according to which file you use. If some strange results appear, report it in your answer :)

Q10: Compare the results obtained in Discotope 2 and 3

Epitope prediction

2025-10-24T11:12:25Z

Carol: Created page with "'''B-cell epitope prediction exercise''' VEGF (vascular endothelial growth factor) is a target in cancer therapies, being the protein responsible for vascularization of tumoral tissue. The murine anti-VEGF antibody has been proved to be effective in blocking VEGF, but it is immunogenic. The Bevacizumab is the commercial, humanized version of the antibody. Let’s reproduce its humanization. Anti-VEGF Humanization The sequence of the murine antibody is: >Light chai..."

'''B-cell epitope prediction exercise'''

VEGF (vascular endothelial growth factor) is a target in cancer therapies, being the protein responsible for vascularization of tumoral tissue.

The murine anti-VEGF antibody has been proved to be effective in blocking VEGF, but it is immunogenic. The Bevacizumab is the commercial, humanized version of the antibody. Let’s reproduce its humanization.

Anti-VEGF Humanization

The sequence of the murine antibody is:

>Light chain
DIQMTQTTSSLSASLGDRVIISCSASQDISNYLNWYQQKPDGTVKVLIYFTSSLHSGVPSRFSGSGSGTDYSLTISNLEPEDIATYYCQ
QYSTVPWTFGGGTKLEIKR

>Heavy Chain
EIQLVQSGPELKQPGETVRISCKASGYTFTNYGMNWVKQAPGKGLKWMGWINTYTGEPTYAADFKRRFTFSLETSASTAYLQISNLK
NDDTATYFCAKYPHYYGSSHWYFDVWGAGTTVTVSS

We will use 2 main tools to perform the humanisation: [[http://www.imgt.org/3Dstructure-DB/cgi/DomainGapAlign.cgi DomainGapAlign]] and PyMol.

The humanisation protocol will follow these steps:

#Identify the human germlines more similar to the murine antibody
#Graft the murine CDRs to the human germline acceptors (obtaining the CDR-grafted antibody)
#Identify all the possible backmutations (all the differences between the murine and CDR grafted antibody
#Build the structural model for the murine and CDR-grafted antibody
#Map the backmutations on the models
#Prioritise the backmutations based on their effect on the structure

Before you start, try to answer to these logical questions, that will help to understand better your task:

1) You don't need to identify the human D gene of the heavy chain that is more similar to the murine one. Why?

2) All backmutations are located in the framework region, not in the CDRs. Why?

3) If you apply all possible backmutations, which antibody would you obtain?

Let's start with our tasks!

'''Q1 - What are the mouse V and J gene for the light and heavy chain?'''

<div class="toccolours mw-collapsible mw-collapsed" style="width:400px; overflow:auto;">
<div style="font-weight:bold;line-height:1.6;">Answer</div>
<div class="mw-collapsible-content mw-collapsed">
Light chain: IGKV10-94 and IGKJ1

Heavy chain: IGHV9-3-1 and IGHJ1
</div></div>

Now we want to identify suitable acceptors, i.e. antibody genes of human origin, for the humanisation. We will again use DomainGapAlign, but this time will select human genes only in the input page

'''Q2 - What are the most similar human V and J gene for the light and heavy chain? What is the similarity?'''

<div class="toccolours mw-collapsible mw-collapsed" style="width:400px; overflow:auto;">
<div style="font-weight:bold;line-height:1.6;">Answer</div>
<div class="mw-collapsible-content mw-collapsed">
Light chain: IGKV1-33 (74.7%) and IGKJ4 (90.9%)

Heavy chain: IGHV7-4 (71.4%) and IGHJ3 (85.7%)
</div></div>

Write down the sequences of the 4 human genes. Keep all the pages open since we will need them later.

Proceed with the humanization using the most similar germlines and the CDR grafting method. In this case, you need to graft the complete mouse CDRs on the human genes. Use the CDR as defined in the DomainGapAlign alignment

'''Q3 - What is the sequence of the CDR-grafted heavy and light chains?'''

<div class="toccolours mw-collapsible mw-collapsed" >
<div style="font-weight:bold;line-height:1.6;">Answer</div>
<div class="mw-collapsible-content mw-collapsed">
>Heavy_CDR
QVQLVQSGSELKKPGASVKVSCKASGYTFTNYGMNWVRQAPGQGLEWMGWINTYTGEPTYAQGFTGRFVFSLDTSVSTAYLQISSLKA EDTAVYYCAKYPHYYGSSHWYFDVWGQGTMVTVSS

>light_CDR
DIQMTQSPSSLSASVGDRVTITCQASQDISNYLNWYQQKPGKAPKLLIYFTSNLETGVPSRFSGSGSGTDFTFTISSLQPEDIATYYCQQYSTVPWTFGGGTKVEIK
</div></div>

Look again at the DomainGapAlign results of the murine antibody on the human germlines. You can use it to identify all possible backmutations - remember that the CDR have been grafted, so they are now 100% murine!

'''Q4: How many possible backmutations are present in the light and heavy chain?'''

<div class="toccolours mw-collapsible mw-collapsed" style="width:400px; overflow:auto;">
<div style="font-weight:bold;line-height:1.6;">Answer</div>
<div class="mw-collapsible-content mw-collapsed">
light: 20 possible backmutations

heavy: 25 possible backmutations
</div></div>

Using [[http://www.cbs.dtu.dk/services/LYRA/ Lyra]], build the models of the murine and CDR-grafted antibody. Rename the two models as murine.pdb and CDR_grafted.pdb.
Open the two models in the same pymol session and align them: click on the "A" button of the murine molecule -> align -> to molecule (*CA) -> CDR_grafted

'''Q5: What is the RMS between the two models?'''

<div class="toccolours mw-collapsible mw-collapsed" style="width:400px; overflow:auto;">
<div style="font-weight:bold;line-height:1.6;">Answer</div>
<div class="mw-collapsible-content mw-collapsed">
Executive: RMS = 0.812 (217 to 217 atoms)
</div></div>

Now, if you display the sequence of the antibodies (small "S" button in the bottom-right part of the screen) they should also be aligned

'''Q6: What templates are used for the murine and CDR_grafted models? Are they the same? Does this affect the accuracy of the models?'''

<div class="toccolours mw-collapsible mw-collapsed" style="width:600px; overflow:auto;">
<div style="font-weight:bold;line-height:1.6;">Answer</div>
<div class="mw-collapsible-content mw-collapsed">
Murine: 1BJ1, 3KLH, 2F19

CDR_grafted: 1BJ1

Since 1BJ1 is used for both models, they might be similar just because they are "copied" from the same template, so the actual RMSD might be larger than it actually appears

</div></div>

'''Q7: in PyMol, identify a few (5 on the heavy, 5 on the light chain) of the possible backmutations in the light and heavy chain and color them red'''

this is a picture of the CDR_grafted model, with all the backmutations colored according to their Blosum90 score

[[File:CDR mut.png]]

The murine and DR_grafted antibody have approximately 80% sequence identity. This will likely result in a partial or complete loss of affinity of the CDR-grafted molecule towards its antigen. By introducing some back mutations, we aim at restoring the affinity. It is important to remember that the more back mutation we introduce, the more we move back towards the original murine antibody, thus increasing the potential immunogenicity of the antibody.

For today exercise, we will focus only on a specific region of the antibody: the FR2 of the light and heavy chain. This region is at the interface of the two chains, and it mediates the packing between them. Even a small difference in the packing may result in a large distortion of the overall ABS.

'''Q8: How many mutations do we observe in the FR2 of the light and heavy chain? '''

<div class="toccolours mw-collapsible mw-collapsed" style="width:400px; overflow:auto;">
<div style="font-weight:bold;line-height:1.6;">Answer</div>
<div class="mw-collapsible-content mw-collapsed">
3 on the heavy chain, 5 on the light chain
</div></div>

'''Q9: Which of these backmutations is more likely to have an impact on the structure? '''

<div class="toccolours mw-collapsible mw-collapsed" style="width:400px; overflow:auto;">
<div style="font-weight:bold;line-height:1.6;">Answer</div>
<div class="mw-collapsible-content mw-collapsed">

DGTV->GKAP : mutations to and from glycine, and mutation to and from proline can have a drastic impact on the structure

</div></div>

Antibody Modelling

2025-10-20T15:12:15Z

Carol: Created page with "'''Humanization of the anti-VEGF antibody''' VEGF (vascular endothelial growth factor) is a target in cancer therapies, being the protein responsible for vascularization of tumoral tissue. The murine anti-VEGF antibody has been proved to be effective in blocking VEGF, but it is immunogenic. The Bevacizumab is the commercial, humanized version of the antibody. Let’s reproduce its humanization. Anti-VEGF Humanization The sequence of the murine antibody is: >Light c..."

'''Humanization of the anti-VEGF antibody'''
VEGF (vascular endothelial growth factor) is a target in cancer therapies, being the protein responsible for vascularization of tumoral tissue.

The murine anti-VEGF antibody has been proved to be effective in blocking VEGF, but it is immunogenic. The Bevacizumab is the commercial, humanized version of the antibody. Let’s reproduce its humanization.

Anti-VEGF Humanization

The sequence of the murine antibody is:

>Light chain
DIQMTQTTSSLSASLGDRVIISCSASQDISNYLNWYQQKPDGTVKVLIYFTSSLHSGVPSRFSGSGSGTDYSLTISNLEPEDIATYYCQ
QYSTVPWTFGGGTKLEIKR

>Heavy Chain
EIQLVQSGPELKQPGETVRISCKASGYTFTNYGMNWVKQAPGKGLKWMGWINTYTGEPTYAADFKRRFTFSLETSASTAYLQISNLK
NDDTATYFCAKYPHYYGSSHWYFDVWGAGTTVTVSS

We will use 2 main tools to perform the humanisation: [[http://www.imgt.org/3Dstructure-DB/cgi/DomainGapAlign.cgi DomainGapAlign]] and PyMol.

The humanisation protocol will follow these steps:

#Identify the human germlines more similar to the murine antibody
#Graft the murine CDRs to the human germline acceptors (obtaining the CDR-grafted antibody)
#Identify all the possible backmutations (all the differences between the murine and CDR grafted antibody
#Build the structural model for the murine and CDR-grafted antibody
#Map the backmutations on the models
#Prioritise the backmutations based on their effect on the structure

Before you start, try to answer to these logical questions, that will help to understand better your task:

1) You don't need to identify the human D gene of the heavy chain that is more similar to the murine one. Why?

2) All backmutations are located in the framework region, not in the CDRs. Why?

3) If you apply all possible backmutations, which antibody would you obtain?

Let's start with our tasks!

'''Q1 - What are the mouse V and J gene for the light and heavy chain?'''

<div class="toccolours mw-collapsible mw-collapsed" style="width:400px; overflow:auto;">
<div style="font-weight:bold;line-height:1.6;">Answer</div>
<div class="mw-collapsible-content mw-collapsed">
Light chain: IGKV10-94 and IGKJ1

Heavy chain: IGHV9-3-1 and IGHJ1
</div></div>

Now we want to identify suitable acceptors, i.e. antibody genes of human origin, for the humanisation. We will again use DomainGapAlign, but this time will select human genes only in the input page

'''Q2 - What are the most similar human V and J gene for the light and heavy chain? What is the similarity?'''

<div class="toccolours mw-collapsible mw-collapsed" style="width:400px; overflow:auto;">
<div style="font-weight:bold;line-height:1.6;">Answer</div>
<div class="mw-collapsible-content mw-collapsed">
Light chain: IGKV1-33 (74.7%) and IGKJ4 (90.9%)

Heavy chain: IGHV7-4 (71.4%) and IGHJ3 (85.7%)
</div></div>

Write down the sequences of the 4 human genes. Keep all the pages open since we will need them later.

Proceed with the humanization using the most similar germlines and the CDR grafting method. In this case, you need to graft the complete mouse CDRs on the human genes. Use the CDR as defined in the DomainGapAlign alignment

'''Q3 - What is the sequence of the CDR-grafted heavy and light chains?'''

<div class="toccolours mw-collapsible mw-collapsed" >
<div style="font-weight:bold;line-height:1.6;">Answer</div>
<div class="mw-collapsible-content mw-collapsed">
>Heavy_CDR
QVQLVQSGSELKKPGASVKVSCKASGYTFTNYGMNWVRQAPGQGLEWMGWINTYTGEPTYAQGFTGRFVFSLDTSVSTAYLQISSLKA EDTAVYYCAKYPHYYGSSHWYFDVWGQGTMVTVSS

>light_CDR
DIQMTQSPSSLSASVGDRVTITCQASQDISNYLNWYQQKPGKAPKLLIYFTSNLETGVPSRFSGSGSGTDFTFTISSLQPEDIATYYCQQYSTVPWTFGGGTKVEIK
</div></div>

Look again at the DomainGapAlign results of the murine antibody on the human germlines. You can use it to identify all possible backmutations - remember that the CDR have been grafted, so they are now 100% murine!

'''Q4: How many possible backmutations are present in the light and heavy chain?'''

<div class="toccolours mw-collapsible mw-collapsed" style="width:400px; overflow:auto;">
<div style="font-weight:bold;line-height:1.6;">Answer</div>
<div class="mw-collapsible-content mw-collapsed">
light: 20 possible backmutations

heavy: 25 possible backmutations
</div></div>

Using [[http://www.cbs.dtu.dk/services/LYRA/ Lyra]], build the models of the murine and CDR-grafted antibody. Rename the two models as murine.pdb and CDR_grafted.pdb.
Open the two models in the same pymol session and align them: click on the "A" button of the murine molecule -> align -> to molecule (*CA) -> CDR_grafted

'''Q5: What is the RMS between the two models?'''

<div class="toccolours mw-collapsible mw-collapsed" style="width:400px; overflow:auto;">
<div style="font-weight:bold;line-height:1.6;">Answer</div>
<div class="mw-collapsible-content mw-collapsed">
Executive: RMS = 0.812 (217 to 217 atoms)
</div></div>

Now, if you display the sequence of the antibodies (small "S" button in the bottom-right part of the screen) they should also be aligned

'''Q6: What templates are used for the murine and CDR_grafted models? Are they the same? Does this affect the accuracy of the models?'''

<div class="toccolours mw-collapsible mw-collapsed" style="width:600px; overflow:auto;">
<div style="font-weight:bold;line-height:1.6;">Answer</div>
<div class="mw-collapsible-content mw-collapsed">
Murine: 1BJ1, 3KLH, 2F19

CDR_grafted: 1BJ1

Since 1BJ1 is used for both models, they might be similar just because they are "copied" from the same template, so the actual RMSD might be larger than it actually appears

</div></div>

'''Q7: in PyMol, identify a few (5 on the heavy, 5 on the light chain) of the possible backmutations in the light and heavy chain and color them red'''

this is a picture of the CDR_grafted model, with all the backmutations colored according to their Blosum90 score

[[File:CDR mut.png]]

The murine and DR_grafted antibody have approximately 80% sequence identity. This will likely result in a partial or complete loss of affinity of the CDR-grafted molecule towards its antigen. By introducing some back mutations, we aim at restoring the affinity. It is important to remember that the more back mutation we introduce, the more we move back towards the original murine antibody, thus increasing the potential immunogenicity of the antibody.

For today exercise, we will focus only on a specific region of the antibody: the FR2 of the light and heavy chain. This region is at the interface of the two chains, and it mediates the packing between them. Even a small difference in the packing may result in a large distortion of the overall ABS.

'''Q8: How many mutations do we observe in the FR2 of the light and heavy chain? '''

<div class="toccolours mw-collapsible mw-collapsed" style="width:400px; overflow:auto;">
<div style="font-weight:bold;line-height:1.6;">Answer</div>
<div class="mw-collapsible-content mw-collapsed">
3 on the heavy chain, 5 on the light chain
</div></div>

'''Q9: Which of these backmutations is more likely to have an impact on the structure? '''

<div class="toccolours mw-collapsible mw-collapsed" style="width:400px; overflow:auto;">
<div style="font-weight:bold;line-height:1.6;">Answer</div>
<div class="mw-collapsible-content mw-collapsed">

DGTV->GKAP : mutations to and from glycine, and mutation to and from proline can have a drastic impact on the structure

</div></div>

IEDB

2025-09-03T01:57:50Z

Carol: /* Epitope Conservancy Analysis of a SARS-CoV2 Peptide Vaccine */

== Immune Epitope DataBase (IEDB) Exercises ==
----

The Immune Epitope DataBase (IEDB) is a very useful resource for researchers of immunology and immunoinformatics. It is a highly organized database of epitopes(or more precisely: epitope assay results) that has a user friendly search interface. It is maintained by the La Jolla Institute for Allergy and Immunology and has a dedicated team of curators and bioinformatitians that have mined the immunological literature. The IEDB is up to date with the immunological literature (within its scope) and is therefore a good place to get an idea of what has been studied and to what extent. Aside from this, they provide prediction tools that can be very useful when no experimental evidence exists. Best of all, it's all free (for academics)!

Today we will focus on building experience in querying the IEDB, so that you may search for data in your own research. Start by going to the [http://www.IEDB.org IEDB home page].

== Sequence Query ==

The goal here is to introduce you to the basic functionalities of the IEDB.

In the home page search (center field on homepage), in the ’Epitope’ field, select ’Linear Epitope’, ’Exact
Match’ and enter in the text box: ’ASNENMETM’. Leave remaining parameters as default and select
’Search’ in the bottom of the page.

*'''Q1: How many epitopes do you find?'''
*'''Q2: From which antigen molecule do the epitopes come from? What about the antigen organism?'''

Under the ’Epitopes’ search tab, inspect the column ’# References’ and note that the output table is sorted
by this column. Click the column header names to change sorting order. Sort again by number of references and
click the ’Details’ number for the epitope with most references. This leads you to a summary page for said
epitope. Note the tabulated T Cell Assay Results.

*'''Q3: What is the number of positive results for the ’qualitative binding’ assay? How about for ’pathogen burden after challenge’?'''

Back on the top of the results page, click around the different tabs(’Epitopes’, ’Antigen’,’Assays’...) for
different vantage points of the results.

*'''Q4: How many entries are under the Assay tab?'''

The ’Assay’ tab result can be further divided by tabs right above the results table(’T Cell Assays’, ’B Cell
Assays’, ’MHC Ligand Assays’).

*'''Q5: How many ’MHC Ligand Assays’ have been performed on the epitopes in question?'''

Applied filters are shown under ’Current Filters’ at the top of the results page. Try removing the ’Positive
Assays Only’ filter by clicking the red ’X’ and pressing ’Search’ (Top Left). You have now included negative
results in your search.

*'''Q6: How many negative ’MHC Ligand Assays’ are added by doing this?'''

You can add the ’Positive Assays Only’ filter back by refining your search. On the left side of the results
page note the search fields(’Epitope’, ’Antigen’, ’Receptor’, ’Assay’...). Scroll down to the ’Assay’ field and
select ’Positive Assays Only’. Scroll back to the top and select click ’Search’.

*'''Q7: What is the ’MHC Ligand Assay’ count now? Does it match your initial count?'''

Finally, inspect the results under the ’Reference’ tab. Click the PMID column entry for any row. This is a
PubMed link to the reference. Back in the result table, sort the resulting references by the date by clicking
the ’Date’ column header.

*'''Q8: What is the time span of publications for the epitopes?'''

Broaden your search. In the ’Epitope’ search field on the left of the results page, change the ’Exact Match’
search to a BLAST search with a 70% sequence homology.

*'''Q9: How many Epitopes does your search yield?'''

'''Pro tip:''' Start with a broad initial search(e.g. all T Cell epitopes) from the home page and then add filters in
steps(in the search field on left of results page). This way you can get a feel for which filter is most restrictive(where
do you lose most epitopes). This is also helpful for debugging a wrong search.

==Neutralizing Ebola Antibodies==

The goal here is to get a clinically interesting dataset by a few clicks on the IEDB.

Starting from the home page search, in the field, select only ’Positive assays only’ and ’B cell assays’. Leave
rest of parameters on default and click 'Search'.

*'''Q10: This should return a large amount of epitopes, how many?'''

Start refining your search using the search fields on the left of the results page. In the ’Organism’ box of
the ’Antigen’ field search for ’Ebolavirus (ID:186538, ID:186539, ID:186540, ID:186541)’. You can also try searching for ’Ebolavirus’ in the
organism finder in the ’Antigen’ field. Click ’Search’ (Top Left) again to add this filter.

*'''Q11: How many Ebola virus epitopes do you see?'''

Further refine your search by looking for only Ebola epitopes reactive in human cells. In the ’Host’ search
field, select ’Human’ and click 'Search' again.

*'''Q12: How many Human reactive Ebola virus epitopes results do you see?'''

Now, let’s filter the ebola epitope set down to only epitopes that have been positively shown to result in
neutralization in a human host. In the ’Assay’ search field, select the ’B Cell Assay’ finder. In the assay
finder, expand the ’Biological Activity’ folder and click ’Neutralization’, ’Apply’ and then search to add this
last filter.

*'''Q13: How many epitopes remain?'''

You now have a highly filtered set of epitopes with clinical interest. In the results page, click the ’Assay’ tab,
find the entry ID ’3218080’ and click it. This is an example of a monoclonal antibody that has shown promise in
the treatment of Ebola in humans. Remember that you can export your search results to a .csv format for later
use.

'''Pro Tip 2:''' When you have your dataset of interest ready for export, note the filters you have applied at the
top of the results page so that you may recreate the dataset later. Also, the results tab you export from influences
what you get.

'''Pro Tip 3:''' You may encounter a ’Bad Request’ error in your browser when working on the IEDB website. Try
clearing your recent browser history (cookies and cached data).

==Population Coverage of a SARS-CoV2 Peptide Vaccine==

We have all been influenced by the coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Fortunately, vaccines have been developed and approved in record time. The currently approved mRNA vaccines of Pfizer and Moderna code for the SARS-CoV-2 Spike Protein, a viral fusion protein that is important for cell adhesion and the induction of protective immunity.

This and the next exercise will be reminiscent of the HCV vaccine development exercise, but we will work with tools from the IEDB and target the SARS-CoV2 spike protein. Here we want to investigate the importance of population coverage in rational peptide vaccine design. To this end, we will work with data from the IEDB and use the Population Coverage Analysis Tool.

From the IEDB home page, search for MHC I restricted T-cell Epitopes in humans from the SARS-Cov-2 Spike glycoprotein antigen.

*'''Q14: How many assay results do you find?'''

In the Antigens tab, select the immunome browser for a mapping of all assay results onto the spike glycoprotein. Observing the "Epitope Assay Counts" plots, we note that most of the protein sequence has been tested. Let us select an epitope subset that has been repeatedly tested with positive assay results(high response frequency). Export the immunome browser results, (and with excel/R/python/...) filter to only include 9-mer peptides, and sort on the lower confidence interval of the Response Frequency.

*'''Q15: What 9-mer has the highest, and most reliable Response Frequency?'''

We will select the top 10 peptides with the highest response frequency as our peptide vaccine candidates. Next we want to test the population coverage of these 10 peptides using the population coverage tool. Population Coverage requires not only the epitope sequences but also by which MHCs they are presented. I have prepared this dataset by predicting binding of the peptides(with NetMHCpan-4.1) to a set of prevalent MHCs and for each peptide, only list the MHCs that bind them strongly(rank<0.5). This data is available in DTU Learn and the file called PopulationCoverageInput

To open the Population Coverage tool: on the IEDB home page, under "Analysis Resource" select "Epitope Analysis Tools" and then "Population Coverage".

Try computing coverage of the 10 peptides to the European population, selecting "Class I seperate" and entering the peptides using Choose File.

*'''Q16: What percentage of the European population does the set of peptides cover?'''

Select "View chart data in table format".

*'''Q17: What percentage of the european population has 0 epitope/HLA hits?'''

Select "View coverage of individual epitope in Europe"

*'''Q18: How many Epitopes have more than 60% coverage of the population, each?'''

Rerun the Population Coverage computation with only the epitopes that each have more than 60% coverage of the European population.

*'''Q19: What coverage do you reach for the European population?'''

Rerun the Population Coverage computation with the same subset, but for the Central African population

*'''Q20: What coverage do you reach for the Central African population?'''

Hopefully this exercise has solidified the idea that one aspect of rational vaccine design is the balancing act between population coverage and cost/complexity/number of peptides.

==Epitope Conservancy Analysis of a SARS-CoV2 Peptide Vaccine==

Another concern when designing a peptide vaccine is the divergence of pathogen strains. A peptide vaccine can achieve excellent population coverage for a single pathogen strain, but a few mutations can render it useless. Therefore we must be aware of the genotypic landscape of current pathogen strains to test the robustness of a vaccine.

Using our epitope set from the previous questions, we want to test the Epitope Conservancy against a compiled set of known SARS-CoV-2 mutations[Xu et. al. Sept. 2020: Variations in SARS-CoV-2 Spike Protein Cell Epitopes and Glycosylation Profiles During Global Transmission Course of COVID-19]. I have compiled SARS-CoV-2 Spike Protein sequence variants (from reference sequence: QHD43416.1), containing 16 frequent mutations in each country until April 26, 2020. (SpikeProteinVariants file in DTU Learn)

To open the Epitope Concervancy tool: on the IEDB home page, under "Analysis Resource" select "Epitope Analysis Tools" and then "Epitope Conservancy Analysis".

We will use a larger set of peptides as input(EpitopeConservancyPeptidesfrom DTU Learn). Input the peptide sequences and the spike protein variant sequences and select "Epitope linear sequence conservancy" and then submit.

*'''Q21: Which Epitope has the lowest number of protein sequence matches at 100%?'''

*'''Q22: Do you think pathogen coverage will be a problem for a vaccine containing these epitopes? Why?'''

The variants were gathered from www.GISAID.org, an organization devoted to sharing data on coronaviruses causing COVID-19. Their front page has a plot showing the number of data submissions: "hCoV-19 Data Sharing via GISAID".

*'''Q23: How many times more submissions have been made since April 26th, 2020 (variants in this exercise)?'''

This indicates that it might be worth repeating this analysis with a more up to date dataset. It could also be interesting to test if variants have emerged whose mutations eliminate epitopes.

----

You should now have a fairly good grasp of the IEDB. It is now your job to
come up with some research questions that you can phrase in the form of an IEDB query.

Done!

IEDB

2025-09-03T01:54:43Z

Carol: /* Epitope Conservancy Analysis of a SARS-CoV2 Peptide Vaccine */

== Immune Epitope DataBase (IEDB) Exercises ==
----

The Immune Epitope DataBase (IEDB) is a very useful resource for researchers of immunology and immunoinformatics. It is a highly organized database of epitopes(or more precisely: epitope assay results) that has a user friendly search interface. It is maintained by the La Jolla Institute for Allergy and Immunology and has a dedicated team of curators and bioinformatitians that have mined the immunological literature. The IEDB is up to date with the immunological literature (within its scope) and is therefore a good place to get an idea of what has been studied and to what extent. Aside from this, they provide prediction tools that can be very useful when no experimental evidence exists. Best of all, it's all free (for academics)!

Today we will focus on building experience in querying the IEDB, so that you may search for data in your own research. Start by going to the [http://www.IEDB.org IEDB home page].

== Sequence Query ==

The goal here is to introduce you to the basic functionalities of the IEDB.

In the home page search (center field on homepage), in the ’Epitope’ field, select ’Linear Epitope’, ’Exact
Match’ and enter in the text box: ’ASNENMETM’. Leave remaining parameters as default and select
’Search’ in the bottom of the page.

*'''Q1: How many epitopes do you find?'''
*'''Q2: From which antigen molecule do the epitopes come from? What about the antigen organism?'''

Under the ’Epitopes’ search tab, inspect the column ’# References’ and note that the output table is sorted
by this column. Click the column header names to change sorting order. Sort again by number of references and
click the ’Details’ number for the epitope with most references. This leads you to a summary page for said
epitope. Note the tabulated T Cell Assay Results.

*'''Q3: What is the number of positive results for the ’qualitative binding’ assay? How about for ’pathogen burden after challenge’?'''

Back on the top of the results page, click around the different tabs(’Epitopes’, ’Antigen’,’Assays’...) for
different vantage points of the results.

*'''Q4: How many entries are under the Assay tab?'''

The ’Assay’ tab result can be further divided by tabs right above the results table(’T Cell Assays’, ’B Cell
Assays’, ’MHC Ligand Assays’).

*'''Q5: How many ’MHC Ligand Assays’ have been performed on the epitopes in question?'''

Applied filters are shown under ’Current Filters’ at the top of the results page. Try removing the ’Positive
Assays Only’ filter by clicking the red ’X’ and pressing ’Search’ (Top Left). You have now included negative
results in your search.

*'''Q6: How many negative ’MHC Ligand Assays’ are added by doing this?'''

You can add the ’Positive Assays Only’ filter back by refining your search. On the left side of the results
page note the search fields(’Epitope’, ’Antigen’, ’Receptor’, ’Assay’...). Scroll down to the ’Assay’ field and
select ’Positive Assays Only’. Scroll back to the top and select click ’Search’.

*'''Q7: What is the ’MHC Ligand Assay’ count now? Does it match your initial count?'''

Finally, inspect the results under the ’Reference’ tab. Click the PMID column entry for any row. This is a
PubMed link to the reference. Back in the result table, sort the resulting references by the date by clicking
the ’Date’ column header.

*'''Q8: What is the time span of publications for the epitopes?'''

Broaden your search. In the ’Epitope’ search field on the left of the results page, change the ’Exact Match’
search to a BLAST search with a 70% sequence homology.

*'''Q9: How many Epitopes does your search yield?'''

'''Pro tip:''' Start with a broad initial search(e.g. all T Cell epitopes) from the home page and then add filters in
steps(in the search field on left of results page). This way you can get a feel for which filter is most restrictive(where
do you lose most epitopes). This is also helpful for debugging a wrong search.

==Neutralizing Ebola Antibodies==

The goal here is to get a clinically interesting dataset by a few clicks on the IEDB.

Starting from the home page search, in the field, select only ’Positive assays only’ and ’B cell assays’. Leave
rest of parameters on default and click 'Search'.

*'''Q10: This should return a large amount of epitopes, how many?'''

Start refining your search using the search fields on the left of the results page. In the ’Organism’ box of
the ’Antigen’ field search for ’Ebolavirus (ID:186538, ID:186539, ID:186540, ID:186541)’. You can also try searching for ’Ebolavirus’ in the
organism finder in the ’Antigen’ field. Click ’Search’ (Top Left) again to add this filter.

*'''Q11: How many Ebola virus epitopes do you see?'''

Further refine your search by looking for only Ebola epitopes reactive in human cells. In the ’Host’ search
field, select ’Human’ and click 'Search' again.

*'''Q12: How many Human reactive Ebola virus epitopes results do you see?'''

Now, let’s filter the ebola epitope set down to only epitopes that have been positively shown to result in
neutralization in a human host. In the ’Assay’ search field, select the ’B Cell Assay’ finder. In the assay
finder, expand the ’Biological Activity’ folder and click ’Neutralization’, ’Apply’ and then search to add this
last filter.

*'''Q13: How many epitopes remain?'''

You now have a highly filtered set of epitopes with clinical interest. In the results page, click the ’Assay’ tab,
find the entry ID ’3218080’ and click it. This is an example of a monoclonal antibody that has shown promise in
the treatment of Ebola in humans. Remember that you can export your search results to a .csv format for later
use.

'''Pro Tip 2:''' When you have your dataset of interest ready for export, note the filters you have applied at the
top of the results page so that you may recreate the dataset later. Also, the results tab you export from influences
what you get.

'''Pro Tip 3:''' You may encounter a ’Bad Request’ error in your browser when working on the IEDB website. Try
clearing your recent browser history (cookies and cached data).

==Population Coverage of a SARS-CoV2 Peptide Vaccine==

We have all been influenced by the coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Fortunately, vaccines have been developed and approved in record time. The currently approved mRNA vaccines of Pfizer and Moderna code for the SARS-CoV-2 Spike Protein, a viral fusion protein that is important for cell adhesion and the induction of protective immunity.

This and the next exercise will be reminiscent of the HCV vaccine development exercise, but we will work with tools from the IEDB and target the SARS-CoV2 spike protein. Here we want to investigate the importance of population coverage in rational peptide vaccine design. To this end, we will work with data from the IEDB and use the Population Coverage Analysis Tool.

From the IEDB home page, search for MHC I restricted T-cell Epitopes in humans from the SARS-Cov-2 Spike glycoprotein antigen.

*'''Q14: How many assay results do you find?'''

In the Antigens tab, select the immunome browser for a mapping of all assay results onto the spike glycoprotein. Observing the "Epitope Assay Counts" plots, we note that most of the protein sequence has been tested. Let us select an epitope subset that has been repeatedly tested with positive assay results(high response frequency). Export the immunome browser results, (and with excel/R/python/...) filter to only include 9-mer peptides, and sort on the lower confidence interval of the Response Frequency.

*'''Q15: What 9-mer has the highest, and most reliable Response Frequency?'''

We will select the top 10 peptides with the highest response frequency as our peptide vaccine candidates. Next we want to test the population coverage of these 10 peptides using the population coverage tool. Population Coverage requires not only the epitope sequences but also by which MHCs they are presented. I have prepared this dataset by predicting binding of the peptides(with NetMHCpan-4.1) to a set of prevalent MHCs and for each peptide, only list the MHCs that bind them strongly(rank<0.5). This data is available in DTU Learn and the file called PopulationCoverageInput

To open the Population Coverage tool: on the IEDB home page, under "Analysis Resource" select "Epitope Analysis Tools" and then "Population Coverage".

Try computing coverage of the 10 peptides to the European population, selecting "Class I seperate" and entering the peptides using Choose File.

*'''Q16: What percentage of the European population does the set of peptides cover?'''

Select "View chart data in table format".

*'''Q17: What percentage of the european population has 0 epitope/HLA hits?'''

Select "View coverage of individual epitope in Europe"

*'''Q18: How many Epitopes have more than 60% coverage of the population, each?'''

Rerun the Population Coverage computation with only the epitopes that each have more than 60% coverage of the European population.

*'''Q19: What coverage do you reach for the European population?'''

Rerun the Population Coverage computation with the same subset, but for the Central African population

*'''Q20: What coverage do you reach for the Central African population?'''

Hopefully this exercise has solidified the idea that one aspect of rational vaccine design is the balancing act between population coverage and cost/complexity/number of peptides.

==Epitope Conservancy Analysis of a SARS-CoV2 Peptide Vaccine==

Another concern when designing a peptide vaccine is the divergence of pathogen strains. A peptide vaccine can achieve excellent population coverage for a single pathogen strain, but a few mutations can render it useless. Therefore we must be aware of the genotypic landscape of current pathogen strains to test the robustness of a vaccine.

Using our epitope set from the previous questions, we want to test the Epitope Conservancy against a recently compiled set of known SARS-CoV-2 mutations[Xu et. al. Sept. 2020: Variations in SARS-CoV-2 Spike Protein Cell Epitopes and Glycosylation Profiles During Global Transmission Course of COVID-19]. I have compiled SARS-CoV-2 Spike Protein sequence variants (from reference sequence: QHD43416.1), containing 16 frequent mutations in each country untill April 26, 2020. This Fasta File is called SpikeProteinVariants in DTU Learn

To open the Epitope Concervancy tool: on the IEDB home page, under "Analysis Resource" select "Epitope Analysis Tools" and then "Epitope Conservancy Analysis".

We will use a larger set of peptides as input(EpitopeConservancyPeptides in DTU Learn). Input the peptide sequences and the spike protein variant sequences and select "Epitope linear sequence conservancy" and then submit.

*'''Q21: Which Epitope has the lowest number of protein sequence matches at 100%?'''

*'''Q22: Do you think pathogen coverage will be a problem for a vaccine containing these epitopes? Why?'''

The variants were gathered from www.GISAID.org, an organization devoted to sharing data on coronaviruses causing COVID-19. Their front page has a plot showing the number of data submissions: "hCoV-19 Data Sharing via GISAID".

*'''Q23: How many times more submissions have been made since April 26th, 2020 (variants in this exercise)?'''

This indicates that it might be worth repeating this analysis with a more up to date dataset. It could also be interesting to test if variants have emerged whose mutations eliminate epitopes.

----

You should now have a fairly good grasp of the IEDB. It is now your job to
come up with some research questions that you can phrase in the form of an IEDB query.

Done!

IEDB

2025-09-03T01:52:58Z

Carol: /* Population Coverage of a SARS-CoV2 Peptide Vaccine */

== Immune Epitope DataBase (IEDB) Exercises ==
----

The Immune Epitope DataBase (IEDB) is a very useful resource for researchers of immunology and immunoinformatics. It is a highly organized database of epitopes(or more precisely: epitope assay results) that has a user friendly search interface. It is maintained by the La Jolla Institute for Allergy and Immunology and has a dedicated team of curators and bioinformatitians that have mined the immunological literature. The IEDB is up to date with the immunological literature (within its scope) and is therefore a good place to get an idea of what has been studied and to what extent. Aside from this, they provide prediction tools that can be very useful when no experimental evidence exists. Best of all, it's all free (for academics)!

Today we will focus on building experience in querying the IEDB, so that you may search for data in your own research. Start by going to the [http://www.IEDB.org IEDB home page].

== Sequence Query ==

The goal here is to introduce you to the basic functionalities of the IEDB.

In the home page search (center field on homepage), in the ’Epitope’ field, select ’Linear Epitope’, ’Exact
Match’ and enter in the text box: ’ASNENMETM’. Leave remaining parameters as default and select
’Search’ in the bottom of the page.

*'''Q1: How many epitopes do you find?'''
*'''Q2: From which antigen molecule do the epitopes come from? What about the antigen organism?'''

Under the ’Epitopes’ search tab, inspect the column ’# References’ and note that the output table is sorted
by this column. Click the column header names to change sorting order. Sort again by number of references and
click the ’Details’ number for the epitope with most references. This leads you to a summary page for said
epitope. Note the tabulated T Cell Assay Results.

*'''Q3: What is the number of positive results for the ’qualitative binding’ assay? How about for ’pathogen burden after challenge’?'''

Back on the top of the results page, click around the different tabs(’Epitopes’, ’Antigen’,’Assays’...) for
different vantage points of the results.

*'''Q4: How many entries are under the Assay tab?'''

The ’Assay’ tab result can be further divided by tabs right above the results table(’T Cell Assays’, ’B Cell
Assays’, ’MHC Ligand Assays’).

*'''Q5: How many ’MHC Ligand Assays’ have been performed on the epitopes in question?'''

Applied filters are shown under ’Current Filters’ at the top of the results page. Try removing the ’Positive
Assays Only’ filter by clicking the red ’X’ and pressing ’Search’ (Top Left). You have now included negative
results in your search.

*'''Q6: How many negative ’MHC Ligand Assays’ are added by doing this?'''

You can add the ’Positive Assays Only’ filter back by refining your search. On the left side of the results
page note the search fields(’Epitope’, ’Antigen’, ’Receptor’, ’Assay’...). Scroll down to the ’Assay’ field and
select ’Positive Assays Only’. Scroll back to the top and select click ’Search’.

*'''Q7: What is the ’MHC Ligand Assay’ count now? Does it match your initial count?'''

Finally, inspect the results under the ’Reference’ tab. Click the PMID column entry for any row. This is a
PubMed link to the reference. Back in the result table, sort the resulting references by the date by clicking
the ’Date’ column header.

*'''Q8: What is the time span of publications for the epitopes?'''

Broaden your search. In the ’Epitope’ search field on the left of the results page, change the ’Exact Match’
search to a BLAST search with a 70% sequence homology.

*'''Q9: How many Epitopes does your search yield?'''

'''Pro tip:''' Start with a broad initial search(e.g. all T Cell epitopes) from the home page and then add filters in
steps(in the search field on left of results page). This way you can get a feel for which filter is most restrictive(where
do you lose most epitopes). This is also helpful for debugging a wrong search.

==Neutralizing Ebola Antibodies==

The goal here is to get a clinically interesting dataset by a few clicks on the IEDB.

Starting from the home page search, in the field, select only ’Positive assays only’ and ’B cell assays’. Leave
rest of parameters on default and click 'Search'.

*'''Q10: This should return a large amount of epitopes, how many?'''

Start refining your search using the search fields on the left of the results page. In the ’Organism’ box of
the ’Antigen’ field search for ’Ebolavirus (ID:186538, ID:186539, ID:186540, ID:186541)’. You can also try searching for ’Ebolavirus’ in the
organism finder in the ’Antigen’ field. Click ’Search’ (Top Left) again to add this filter.

*'''Q11: How many Ebola virus epitopes do you see?'''

Further refine your search by looking for only Ebola epitopes reactive in human cells. In the ’Host’ search
field, select ’Human’ and click 'Search' again.

*'''Q12: How many Human reactive Ebola virus epitopes results do you see?'''

Now, let’s filter the ebola epitope set down to only epitopes that have been positively shown to result in
neutralization in a human host. In the ’Assay’ search field, select the ’B Cell Assay’ finder. In the assay
finder, expand the ’Biological Activity’ folder and click ’Neutralization’, ’Apply’ and then search to add this
last filter.

*'''Q13: How many epitopes remain?'''

You now have a highly filtered set of epitopes with clinical interest. In the results page, click the ’Assay’ tab,
find the entry ID ’3218080’ and click it. This is an example of a monoclonal antibody that has shown promise in
the treatment of Ebola in humans. Remember that you can export your search results to a .csv format for later
use.

'''Pro Tip 2:''' When you have your dataset of interest ready for export, note the filters you have applied at the
top of the results page so that you may recreate the dataset later. Also, the results tab you export from influences
what you get.

'''Pro Tip 3:''' You may encounter a ’Bad Request’ error in your browser when working on the IEDB website. Try
clearing your recent browser history (cookies and cached data).

==Population Coverage of a SARS-CoV2 Peptide Vaccine==

We have all been influenced by the coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Fortunately, vaccines have been developed and approved in record time. The currently approved mRNA vaccines of Pfizer and Moderna code for the SARS-CoV-2 Spike Protein, a viral fusion protein that is important for cell adhesion and the induction of protective immunity.

This and the next exercise will be reminiscent of the HCV vaccine development exercise, but we will work with tools from the IEDB and target the SARS-CoV2 spike protein. Here we want to investigate the importance of population coverage in rational peptide vaccine design. To this end, we will work with data from the IEDB and use the Population Coverage Analysis Tool.

From the IEDB home page, search for MHC I restricted T-cell Epitopes in humans from the SARS-Cov-2 Spike glycoprotein antigen.

*'''Q14: How many assay results do you find?'''

In the Antigens tab, select the immunome browser for a mapping of all assay results onto the spike glycoprotein. Observing the "Epitope Assay Counts" plots, we note that most of the protein sequence has been tested. Let us select an epitope subset that has been repeatedly tested with positive assay results(high response frequency). Export the immunome browser results, (and with excel/R/python/...) filter to only include 9-mer peptides, and sort on the lower confidence interval of the Response Frequency.

*'''Q15: What 9-mer has the highest, and most reliable Response Frequency?'''

We will select the top 10 peptides with the highest response frequency as our peptide vaccine candidates. Next we want to test the population coverage of these 10 peptides using the population coverage tool. Population Coverage requires not only the epitope sequences but also by which MHCs they are presented. I have prepared this dataset by predicting binding of the peptides(with NetMHCpan-4.1) to a set of prevalent MHCs and for each peptide, only list the MHCs that bind them strongly(rank<0.5). This data is available in DTU Learn and the file called PopulationCoverageInput

To open the Population Coverage tool: on the IEDB home page, under "Analysis Resource" select "Epitope Analysis Tools" and then "Population Coverage".

Try computing coverage of the 10 peptides to the European population, selecting "Class I seperate" and entering the peptides using Choose File.

*'''Q16: What percentage of the European population does the set of peptides cover?'''

Select "View chart data in table format".

*'''Q17: What percentage of the european population has 0 epitope/HLA hits?'''

Select "View coverage of individual epitope in Europe"

*'''Q18: How many Epitopes have more than 60% coverage of the population, each?'''

Rerun the Population Coverage computation with only the epitopes that each have more than 60% coverage of the European population.

*'''Q19: What coverage do you reach for the European population?'''

Rerun the Population Coverage computation with the same subset, but for the Central African population

*'''Q20: What coverage do you reach for the Central African population?'''

Hopefully this exercise has solidified the idea that one aspect of rational vaccine design is the balancing act between population coverage and cost/complexity/number of peptides.

==Epitope Conservancy Analysis of a SARS-CoV2 Peptide Vaccine==

Another concern when designing a peptide vaccine is the divergence of pathogen strains. A peptide vaccine can achieve excellent population coverage for a single pathogen strain, but a few mutations can render it useless. Therefore we must be aware of the genotypic landscape of current pathogen strains to test the robustness of a vaccine.

Using our epitope set from the previous questions, we want to test the Epitope Conservancy against a recently compiled set of known SARS-CoV-2 mutations[Xu et. al. Sept. 2020: Variations in SARS-CoV-2 Spike Protein Cell Epitopes and Glycosylation Profiles During Global Transmission Course of COVID-19]. I have compiled SARS-CoV-2 Spike Protein sequence variants (from reference sequence: QHD43416.1), containing 16 frequent mutations in each country untill April 26, 2020. This Fasta File can be found here. [http://www.cbs.dtu.dk/courses/27685.imm/presentations/Carol/IEDB_Ex/SpikeProteinVariants.fasta SpikeProteinVariants]

To open the Epitope Concervancy tool: on the IEDB home page, under "Analysis Resource" select "Epitope Analysis Tools" and then "Epitope Conservancy Analysis".

We will use a larger set of peptides as input([http://www.cbs.dtu.dk/courses/27685.imm/presentations/Carol/IEDB_Ex/Epitopes_EpitopeConservancyInput.fasta EpitopeConservancyPeptides]). Input the peptide sequences and the spike protein variant sequences and select "Epitope linear sequence conservancy" and then submit.

*'''Q21: Which Epitope has the lowest number of protein sequence matches at 100%?'''

*'''Q22: Do you think pathogen coverage will be a problem for a vaccine containing these epitopes? Why?'''

The variants were gathered from www.GISAID.org, an organization devoted to sharing data on coronaviruses causing COVID-19. Their front page has a plot showing the number of data submissions: "hCoV-19 Data Sharing via GISAID".

*'''Q23: How many times more submissions have been made since April 26th, 2020 (variants in this exercise)?'''

This indicates that it might be worth repeating this analysis with a more up to date dataset. It could also be interesting to test if variants have emerged whose mutations eliminate epitopes.

----

You should now have a fairly good grasp of the IEDB. It is now your job to
come up with some research questions that you can phrase in the form of an IEDB query.

Done!

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-29T10:15:07Z

Carol: /* Wednesday, Nov 5 — Predictions in Autoimmunity */

== General information ==

=== Where and when ===

Wednesday from 9 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 9:00'''. Classess will start at 9am unless specified. The first hour of the course will be dedicated to course-preparation. Including some videos or paper reading material

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises, and part 2 will cover a group-based research project with the output being a poster presentation on the last day of the course.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

AI bots are allowed but you should state in your answer where and how you have used them. A word of wisdom here: AI generative models will give very general answers which might make you loose precious time of the exam, so be careful on their use.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/271397

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — Antigen Processing and Presentation ===
:'''Lecture:''' ''Antigen Processing and Presentation'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — MHC binding predictions part 1 ===
:'''Lecture:''' ''MHC binding predictions Part 1'' — Morten Nielsen
:'''Slides:''' on DTU Learn.

:'''Exercises:'''

=== Wednesday, Sep 24 — MHC binding predictions part 2 ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Allergenicity prediction ===

:'''Lecture:''' ''Allergenicity prediction'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — BCR and TCR structure predictions ===
:'''Workshop:''' ''BCR and TCR structure predictions'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — B Cell epitope predictions ===
:'''Lecture:''' ''B Cell epitope predictions'' — Paolo Marcatili
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — TCR interaction models ===
:'''Lecture:''' ''TCR interaction models'' — TBD
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 3 — Poster session ===

:Poster presentations will be '''starting at 8:00am'''

:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-29T10:14:20Z

Carol: /* Wednesday, Oct 29 — Vaccine design */

== General information ==

=== Where and when ===

Wednesday from 9 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 9:00'''. Classess will start at 9am unless specified. The first hour of the course will be dedicated to course-preparation. Including some videos or paper reading material

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises, and part 2 will cover a group-based research project with the output being a poster presentation on the last day of the course.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

AI bots are allowed but you should state in your answer where and how you have used them. A word of wisdom here: AI generative models will give very general answers which might make you loose precious time of the exam, so be careful on their use.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/271397

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — Antigen Processing and Presentation ===
:'''Lecture:''' ''Antigen Processing and Presentation'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — MHC binding predictions part 1 ===
:'''Lecture:''' ''MHC binding predictions Part 1'' — Morten Nielsen
:'''Slides:''' on DTU Learn.

:'''Exercises:'''

=== Wednesday, Sep 24 — MHC binding predictions part 2 ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Allergenicity prediction ===

:'''Lecture:''' ''Allergenicity prediction'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — BCR and TCR structure predictions ===
:'''Workshop:''' ''BCR and TCR structure predictions'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — B Cell epitope predictions ===
:'''Lecture:''' ''B Cell epitope predictions'' — Paolo Marcatili
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 3 — Poster session ===

:Poster presentations will be '''starting at 8:00am'''

:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-29T10:13:53Z

Carol: /* Wednesday, Oct 22 — TCR interaction models and TCR repertoires */

== General information ==

=== Where and when ===

Wednesday from 9 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 9:00'''. Classess will start at 9am unless specified. The first hour of the course will be dedicated to course-preparation. Including some videos or paper reading material

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises, and part 2 will cover a group-based research project with the output being a poster presentation on the last day of the course.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

AI bots are allowed but you should state in your answer where and how you have used them. A word of wisdom here: AI generative models will give very general answers which might make you loose precious time of the exam, so be careful on their use.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/271397

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — Antigen Processing and Presentation ===
:'''Lecture:''' ''Antigen Processing and Presentation'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — MHC binding predictions part 1 ===
:'''Lecture:''' ''MHC binding predictions Part 1'' — Morten Nielsen
:'''Slides:''' on DTU Learn.

:'''Exercises:'''

=== Wednesday, Sep 24 — MHC binding predictions part 2 ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Allergenicity prediction ===

:'''Lecture:''' ''Allergenicity prediction'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — BCR and TCR structure predictions ===
:'''Workshop:''' ''BCR and TCR structure predictions'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 3 — Poster session ===

:Poster presentations will be '''starting at 8:00am'''

:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-29T10:13:10Z

Carol: /* Wednesday, Oct 8 — Antigen Processing and Immunogenicity */

== General information ==

=== Where and when ===

Wednesday from 9 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 9:00'''. Classess will start at 9am unless specified. The first hour of the course will be dedicated to course-preparation. Including some videos or paper reading material

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises, and part 2 will cover a group-based research project with the output being a poster presentation on the last day of the course.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

AI bots are allowed but you should state in your answer where and how you have used them. A word of wisdom here: AI generative models will give very general answers which might make you loose precious time of the exam, so be careful on their use.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/271397

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — Antigen Processing and Presentation ===
:'''Lecture:''' ''Antigen Processing and Presentation'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — MHC binding predictions part 1 ===
:'''Lecture:''' ''MHC binding predictions Part 1'' — Morten Nielsen
:'''Slides:''' on DTU Learn.

:'''Exercises:'''

=== Wednesday, Sep 24 — MHC binding predictions part 2 ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Allergenicity prediction ===

:'''Lecture:''' ''Allergenicity prediction'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 3 — Poster session ===

:Poster presentations will be '''starting at 8:00am'''

:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-29T10:12:37Z

Carol: /* Wednesday, Oct 1 — MHC binding predictions */

== General information ==

=== Where and when ===

Wednesday from 9 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 9:00'''. Classess will start at 9am unless specified. The first hour of the course will be dedicated to course-preparation. Including some videos or paper reading material

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises, and part 2 will cover a group-based research project with the output being a poster presentation on the last day of the course.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

AI bots are allowed but you should state in your answer where and how you have used them. A word of wisdom here: AI generative models will give very general answers which might make you loose precious time of the exam, so be careful on their use.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/271397

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — Antigen Processing and Presentation ===
:'''Lecture:''' ''Antigen Processing and Presentation'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — MHC binding predictions part 1 ===
:'''Lecture:''' ''MHC binding predictions Part 1'' — Morten Nielsen
:'''Slides:''' on DTU Learn.

:'''Exercises:'''

=== Wednesday, Sep 24 — MHC binding predictions part 2 ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 3 — Poster session ===

:Poster presentations will be '''starting at 8:00am'''

:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-29T10:12:21Z

Carol: /* Wednesday, Sep 17 — MHC binding predictions */

== General information ==

=== Where and when ===

Wednesday from 9 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 9:00'''. Classess will start at 9am unless specified. The first hour of the course will be dedicated to course-preparation. Including some videos or paper reading material

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises, and part 2 will cover a group-based research project with the output being a poster presentation on the last day of the course.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

AI bots are allowed but you should state in your answer where and how you have used them. A word of wisdom here: AI generative models will give very general answers which might make you loose precious time of the exam, so be careful on their use.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/271397

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — Antigen Processing and Presentation ===
:'''Lecture:''' ''Antigen Processing and Presentation'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — MHC binding predictions part 1 ===
:'''Lecture:''' ''MHC binding predictions Part 1'' — Morten Nielsen
:'''Slides:''' on DTU Learn.

:'''Exercises:'''

=== Wednesday, Sep 24 — MHC binding predictions part 2 ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 3 — Poster session ===

:Poster presentations will be '''starting at 8:00am'''

:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-29T10:12:12Z

Carol: /* Wednesday, Sep 24 — MHC binding predictions */

== General information ==

=== Where and when ===

Wednesday from 9 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 9:00'''. Classess will start at 9am unless specified. The first hour of the course will be dedicated to course-preparation. Including some videos or paper reading material

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises, and part 2 will cover a group-based research project with the output being a poster presentation on the last day of the course.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

AI bots are allowed but you should state in your answer where and how you have used them. A word of wisdom here: AI generative models will give very general answers which might make you loose precious time of the exam, so be careful on their use.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/271397

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — Antigen Processing and Presentation ===
:'''Lecture:''' ''Antigen Processing and Presentation'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions Part 1'' — Morten Nielsen
:'''Slides:''' on DTU Learn.

:'''Exercises:'''

=== Wednesday, Sep 24 — MHC binding predictions part 2 ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 3 — Poster session ===

:Poster presentations will be '''starting at 8:00am'''

:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-29T10:11:56Z

Carol: /* Wednesday, Sep 17 — Antigen Processing and Presentation */

== General information ==

=== Where and when ===

Wednesday from 9 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 9:00'''. Classess will start at 9am unless specified. The first hour of the course will be dedicated to course-preparation. Including some videos or paper reading material

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises, and part 2 will cover a group-based research project with the output being a poster presentation on the last day of the course.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

AI bots are allowed but you should state in your answer where and how you have used them. A word of wisdom here: AI generative models will give very general answers which might make you loose precious time of the exam, so be careful on their use.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/271397

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — Antigen Processing and Presentation ===
:'''Lecture:''' ''Antigen Processing and Presentation'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions Part 1'' — Morten Nielsen
:'''Slides:''' on DTU Learn.

:'''Exercises:'''

=== Wednesday, Sep 24 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 3 — Poster session ===

:Poster presentations will be '''starting at 8:00am'''

:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-29T10:11:23Z

Carol: /* Wednesday, Sep 17 — Allergenicity prediction */

== General information ==

=== Where and when ===

Wednesday from 9 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 9:00'''. Classess will start at 9am unless specified. The first hour of the course will be dedicated to course-preparation. Including some videos or paper reading material

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises, and part 2 will cover a group-based research project with the output being a poster presentation on the last day of the course.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

AI bots are allowed but you should state in your answer where and how you have used them. A word of wisdom here: AI generative models will give very general answers which might make you loose precious time of the exam, so be careful on their use.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/271397

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — Antigen Processing and Presentation ===
:'''Lecture:''' ''Antigen Processing and Presentation'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — Antigen Processing and Presentation ===
:'''Lecture:''' ''Antigen Processing and Presentation Part 1'' — Morten Nielsen
:'''Slides:''' on DTU Learn.

:'''Exercises:'''

=== Wednesday, Sep 24 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 3 — Poster session ===

:Poster presentations will be '''starting at 8:00am'''

:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-29T10:10:20Z

Carol: /* Wednesday, Sep 10 — B cell epitopes */

== General information ==

=== Where and when ===

Wednesday from 9 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 9:00'''. Classess will start at 9am unless specified. The first hour of the course will be dedicated to course-preparation. Including some videos or paper reading material

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises, and part 2 will cover a group-based research project with the output being a poster presentation on the last day of the course.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

AI bots are allowed but you should state in your answer where and how you have used them. A word of wisdom here: AI generative models will give very general answers which might make you loose precious time of the exam, so be careful on their use.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/271397

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — Antigen Processing and Presentation ===
:'''Lecture:''' ''Antigen Processing and Presentation'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 24 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 3 — Poster session ===

:Poster presentations will be '''starting at 8:00am'''

:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-29T10:09:57Z

Carol: /* Wednesday, Sep 10 — B cell epitopes */

== General information ==

=== Where and when ===

Wednesday from 9 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 9:00'''. Classess will start at 9am unless specified. The first hour of the course will be dedicated to course-preparation. Including some videos or paper reading material

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises, and part 2 will cover a group-based research project with the output being a poster presentation on the last day of the course.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

AI bots are allowed but you should state in your answer where and how you have used them. A word of wisdom here: AI generative models will give very general answers which might make you loose precious time of the exam, so be careful on their use.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/271397

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — B cell epitopes ===
:'''Lecture:''' ''Antigen Processing and Presentation'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 24 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 3 — Poster session ===

:Poster presentations will be '''starting at 8:00am'''

:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-07T12:21:32Z

Carol: /* DTU Learn Link */

== General information ==

=== Where and when ===

Wednesday from 9 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 9:00'''. Classess will start at 9am unless specified. The first hour of the course will be dedicated to course-preparation. Including some videos or paper reading material

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises, and part 2 will cover a group-based research project with the output being a poster presentation on the last day of the course.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

AI bots are allowed but you should state in your answer where and how you have used them. A word of wisdom here: AI generative models will give very general answers which might make you loose precious time of the exam, so be careful on their use.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/271397

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — B cell epitopes ===
:'''Lecture:''' ''B cell receptors and B cell epitopes'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 24 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 3 — Poster session ===

:Poster presentations will be '''starting at 8:00am'''

:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-07T12:18:07Z

Carol: /* Exam */

== General information ==

=== Where and when ===

Wednesday from 9 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 9:00'''. Classess will start at 9am unless specified. The first hour of the course will be dedicated to course-preparation. Including some videos or paper reading material

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises, and part 2 will cover a group-based research project with the output being a poster presentation on the last day of the course.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

AI bots are allowed but you should state in your answer where and how you have used them. A word of wisdom here: AI generative models will give very general answers which might make you loose precious time of the exam, so be careful on their use.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/215856

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — B cell epitopes ===
:'''Lecture:''' ''B cell receptors and B cell epitopes'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 24 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 3 — Poster session ===

:Poster presentations will be '''starting at 8:00am'''

:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-07T12:09:01Z

Carol: /* Course content */

== General information ==

=== Where and when ===

Wednesday from 9 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 9:00'''. Classess will start at 9am unless specified. The first hour of the course will be dedicated to course-preparation. Including some videos or paper reading material

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises, and part 2 will cover a group-based research project with the output being a poster presentation on the last day of the course.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

Chatbots are allowed but you should state in your answer that you have used them.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/215856

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — B cell epitopes ===
:'''Lecture:''' ''B cell receptors and B cell epitopes'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 24 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 3 — Poster session ===

:Poster presentations will be '''starting at 8:00am'''

:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-07T12:06:50Z

Carol: /* Wednesday, Dec 3 — Poster session */

== General information ==

=== Where and when ===

Wednesday from 9 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 9:00'''. Classess will start at 9am unless specified. The first hour of the course will be dedicated to course-preparation. Including some videos or paper reading material

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises and part 2 will cover group-based project work aiming at creating a full project workflow with the output being a poster presentation.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

Chatbots are allowed but you should state in your answer that you have used them.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/215856

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — B cell epitopes ===
:'''Lecture:''' ''B cell receptors and B cell epitopes'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 24 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 3 — Poster session ===

:Poster presentations will be '''starting at 8:00am'''

:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-07T12:06:38Z

Carol: /* Wednesday, Dec 3 — Poster session */

== General information ==

=== Where and when ===

Wednesday from 9 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 9:00'''. Classess will start at 9am unless specified. The first hour of the course will be dedicated to course-preparation. Including some videos or paper reading material

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises and part 2 will cover group-based project work aiming at creating a full project workflow with the output being a poster presentation.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

Chatbots are allowed but you should state in your answer that you have used them.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/215856

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — B cell epitopes ===
:'''Lecture:''' ''B cell receptors and B cell epitopes'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 24 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 3 — Poster session ===
Poster presentations will be '''starting at 8:00am'''

:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-07T12:06:25Z

Carol: /* Wednesday, Dec 3 — Poster session */

== General information ==

=== Where and when ===

Wednesday from 9 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 9:00'''. Classess will start at 9am unless specified. The first hour of the course will be dedicated to course-preparation. Including some videos or paper reading material

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises and part 2 will cover group-based project work aiming at creating a full project workflow with the output being a poster presentation.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

Chatbots are allowed but you should state in your answer that you have used them.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/215856

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — B cell epitopes ===
:'''Lecture:''' ''B cell receptors and B cell epitopes'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 24 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 3 — Poster session ===
Poster presentations will be starting at '''8:00am'''

:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-07T12:05:27Z

Carol:

== General information ==

=== Where and when ===

Wednesday from 9 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 9:00'''. Classess will start at 9am unless specified. The first hour of the course will be dedicated to course-preparation. Including some videos or paper reading material

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises and part 2 will cover group-based project work aiming at creating a full project workflow with the output being a poster presentation.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

Chatbots are allowed but you should state in your answer that you have used them.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/215856

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — B cell epitopes ===
:'''Lecture:''' ''B cell receptors and B cell epitopes'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 24 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 3 — Poster session ===
'''Starting at 8:00'''

:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-07T12:04:58Z

Carol:

== General information ==

=== Where and when ===

Wednesday from 9 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 9:00'''. Classess will start at 9am unless specified. The first hour of the course will be dedicated to course-preparation. Including some videos or paper reading material

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises and part 2 will cover group-based project work aiming at creating a full project workflow with the output being a poster presentation.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

Chatbots are allowed but you should state in your answer that you have used them.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/215856

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — B cell epitopes ===
:'''Lecture:''' ''B cell receptors and B cell epitopes'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 24 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 3 — Poster session === '''Starting at 8:00'''

:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-07T11:55:24Z

Carol: /* Wednesday, Dec 5 — Poster session */

== General information ==

=== Where and when ===

Wednesday from 8 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 8:00'''.

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises and part 2 will cover group-based project work aiming at creating a full project workflow with the output being a poster presentation.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

Chatbots are allowed but you should state in your answer that you have used them.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/215856

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — B cell epitopes ===
:'''Lecture:''' ''B cell receptors and B cell epitopes'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 24 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 3 — Poster session ===
:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-07T11:54:21Z

Carol: /* Course content */

== General information ==

=== Where and when ===

Wednesday from 8 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 8:00'''.

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises and part 2 will cover group-based project work aiming at creating a full project workflow with the output being a poster presentation.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

Chatbots are allowed but you should state in your answer that you have used them.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/215856

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — B cell epitopes ===
:'''Lecture:''' ''B cell receptors and B cell epitopes'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 24 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 5 — Poster session ===
:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-07T11:53:12Z

Carol:

== General information ==

=== Where and when ===

Wednesday from 8 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 8:00'''.

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises and part 2 will cover group-based project work aiming at creating a full project workflow.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

Chatbots are allowed but you should state in your answer that you have used them.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/215856

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 3 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 10 — B cell epitopes ===
:'''Lecture:''' ''B cell receptors and B cell epitopes'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 17 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 24 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 1 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 8 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 22 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 29 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 5 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 12 — Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 19 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 26 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 5 — Poster session ===
:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-07T11:14:11Z

Carol:

== General information ==

=== Where and when ===

Wednesday from 8 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 3 at 8:00'''.

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/english/person/sebastian-nymann-deleuran?id=117549&entity=profile Sebastian Nymann Deleuran] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises and part 2 will cover group-based project work aiming at creating a full project workflow.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

Chatbots are allowed but you should state in your answer that you have used them.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/215856

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 4 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 11 — B cell epitopes ===
:'''Lecture:''' ''B cell receptors and B cell epitopes'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 18 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 25 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 2 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 9 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 23 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 30 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 6 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 13 — Beginning Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 20 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 27 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 4 — Project work poster session ===
:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2025

2025-08-07T11:10:30Z

Carol: Created page with "== General information == === Where and when === Wednesday from 8 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 4 at 8:00'''. === Teachers === * [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible. * [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible. === Teaching assistant === * [https://w..."

== General information ==

=== Where and when ===

Wednesday from 8 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 4 at 8:00'''.

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/person/astrid-brix-saksager?id=118546&entity=profile Astrid Brix Saksager] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises and part 2 will cover group-based project work aiming at creating a full project workflow.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

Chatbots are allowed but you should state in your answer that you have used them.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/215856

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 4 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 11 — B cell epitopes ===
:'''Lecture:''' ''B cell receptors and B cell epitopes'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 18 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 25 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 2 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 9 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 23 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 30 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 6 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 13 — Beginning Project work ===
:'''Lecture:''' No LECTURE

=== Wednesday, Nov 20 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 27 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 4 — Project work poster session ===
:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2024

2024-11-11T13:24:44Z

Carol: /* Wednesday, Nov 13 — Beginning Project work */

22145 Immunological Bioinformatics Course Programme Fall 2024

2024-11-11T13:24:21Z

Carol: /* Wednesday, Nov 6 — Predictions in Autoimmunity */

== General information ==

=== Where and when ===

Wednesday from 8 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 4 at 8:00'''.

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/person/astrid-brix-saksager?id=118546&entity=profile Astrid Brix Saksager] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises and part 2 will cover group-based project work aiming at creating a full project workflow.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

Chatbots are allowed but you should state in your answer that you have used them.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/215856

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 4 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 11 — B cell epitopes ===
:'''Lecture:''' ''B cell receptors and B cell epitopes'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 18 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 25 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 2 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 9 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 23 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 30 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 6 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
: ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 13 — Beginning Project work ===
:'''Lecture:'''
:'''Slides:'''
:'''Exercise:'''

=== Wednesday, Nov 20 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 27 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 4 — Project work poster session ===
:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2024

2024-11-11T13:23:46Z

Carol: /* Wednesday, Nov 13 — Beginning Project work */

== General information ==

=== Where and when ===

Wednesday from 8 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 4 at 8:00'''.

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/person/astrid-brix-saksager?id=118546&entity=profile Astrid Brix Saksager] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises and part 2 will cover group-based project work aiming at creating a full project workflow.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

Chatbots are allowed but you should state in your answer that you have used them.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/215856

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 4 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 11 — B cell epitopes ===
:'''Lecture:''' ''B cell receptors and B cell epitopes'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 18 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 25 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 2 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 9 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 23 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 30 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 6 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 13 — Beginning Project work ===
:'''Lecture:'''
:'''Slides:'''
:'''Exercise:'''

=== Wednesday, Nov 20 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 27 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 4 — Project work poster session ===
:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2024

2024-08-27T17:57:43Z

Carol: /* Wednesday, Oct 23 — TCR interaction models and TCR repertoires */

== General information ==

=== Where and when ===

Wednesday from 8 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 4 at 8:00'''.

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/person/astrid-brix-saksager?id=118546&entity=profile Astrid Brix Saksager] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises and part 2 will cover group-based project work aiming at creating a full project workflow.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

Chatbots are allowed but you should state in your answer that you have used them.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/215856

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 4 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 11 — B cell epitopes ===
:'''Lecture:''' ''B cell receptors and B cell epitopes'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 18 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 25 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 2 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 9 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 23 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:'''Slides:''' on DTU Learn.
:''' GitHub link:'''


=== Wednesday, Oct 30 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 6 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 13 — Beginning Project work ===
:'''Lecture:''' ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercise:'''

=== Wednesday, Nov 20 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 27 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 4 — Project work poster session ===
:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2024

2024-08-27T17:56:48Z

Carol: /* Wednesday, Oct 23 — TCR interaction models and TCR repertoires */

== General information ==

=== Where and when ===

Wednesday from 8 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 4 at 8:00'''.

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/person/astrid-brix-saksager?id=118546&entity=profile Astrid Brix Saksager] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises and part 2 will cover group-based project work aiming at creating a full project workflow.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

Chatbots are allowed but you should state in your answer that you have used them.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/215856

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 4 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 11 — B cell epitopes ===
:'''Lecture:''' ''B cell receptors and B cell epitopes'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 18 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 25 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 2 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 9 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 23 — TCR interaction models and TCR repertoires ===
:'''Workshop:''' ''TCR interaction models and TCR repertoires'' — Leon Eyrich Jessen
:''' Class material will be shared through the GitHub link:'''


=== Wednesday, Oct 30 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 6 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 13 — Beginning Project work ===
:'''Lecture:''' ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercise:'''

=== Wednesday, Nov 20 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 27 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 4 — Project work poster session ===
:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2024

2024-08-25T20:36:56Z

Carol: /* Wednesday, Nov 6 — Weight matrices and other prediction methods */

== General information ==

=== Where and when ===

Wednesday from 8 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 4 at 8:00'''.

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/person/astrid-brix-saksager?id=118546&entity=profile Astrid Brix Saksager] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises and part 2 will cover group-based project work aiming at creating a full project workflow.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

Chatbots are allowed but you should state in your answer that you have used them.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/215856

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 4 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 11 — B cell epitopes ===
:'''Lecture:''' ''B cell receptors and B cell epitopes'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 18 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 25 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 2 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 9 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 23 — TCR interaction models and TCR repertoires ===
:'''Lecture:''' ''TCR interaction models and TCR repertoires'' — Invited Speaker (TBD)
:'''Exercise:'''


=== Wednesday, Oct 30 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 6 — Predictions in Autoimmunity ===
:'''Lecture:''' ''Case study: Autoimmunity'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercises:'''



=== Wednesday, Nov 13 — Beginning Project work ===
:'''Lecture:''' ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercise:'''

=== Wednesday, Nov 20 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 27 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 4 — Project work poster session ===
:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2024

2024-08-25T20:35:19Z

Carol: /* Wednesday, Nov 13 — Beginning Project work */

== General information ==

=== Where and when ===

Wednesday from 8 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 4 at 8:00'''.

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/person/astrid-brix-saksager?id=118546&entity=profile Astrid Brix Saksager] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises and part 2 will cover group-based project work aiming at creating a full project workflow.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

Chatbots are allowed but you should state in your answer that you have used them.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/215856

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 4 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 11 — B cell epitopes ===
:'''Lecture:''' ''B cell receptors and B cell epitopes'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 18 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 25 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 2 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 9 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 23 — TCR interaction models and TCR repertoires ===
:'''Lecture:''' ''TCR interaction models and TCR repertoires'' — Invited Speaker (TBD)
:'''Exercise:'''


=== Wednesday, Oct 30 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 6 — Weight matrices and other prediction methods ===
:'''Lecture:''' ''Introduction to prediction methods, especially Weight Matrices'' — Henrik Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercises:'''


=== Wednesday, Nov 13 — Beginning Project work ===
:'''Lecture:''' ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercise:'''

=== Wednesday, Nov 20 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 27 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 4 — Project work poster session ===
:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.

22145 Immunological Bioinformatics Course Programme Fall 2024

2024-08-25T20:35:09Z

Carol: /* Wednesday, Oct 23 — TCR interaction models and TCR repertoires */

== General information ==

=== Where and when ===

Wednesday from 8 to 12 in '''building 208, holdlokale 3/065''', starting on '''Wednesday, Sep 4 at 8:00'''.

=== Teachers ===

* [https://www.dtu.dk/Person/cwis?id=142840&entity=profile Carolina Barra Quaglia] — Associate professor, course responsible.

* [https://www.dtu.dk/person/morten-nielsen?id=5973&entity=profile Morten Nielsen] — Professor, course responsible.

=== Teaching assistant ===

* [https://www.dtu.dk/person/astrid-brix-saksager?id=118546&entity=profile Astrid Brix Saksager] — PhD student

=== Course content ===

The course aims to introduce the students to state-of-the-art methods within computational immunology.

There is a strong focus on introducing the methods in context with immunology as a domain-specific knowledge area. Furthermore, an introduction to the theory of the methods will be followed by practical exercises, enabling the student to independently perform analyses. The course covers immunological bioinformatics and computational vaccinology with an outlook on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts. Part 1 covers lectures and group-based exercises and part 2 will cover group-based project work aiming at creating a full project workflow.

See also [http://kurser.dtu.dk/course/22145 the course base about 22145].

=== Curriculum ===

There is no formal textbook. The curricula consist of lectures and exercises performed in class, supplemented with various papers and book chapters which will be made available on DTU Learn. Please note that ''all'' exercise guides are mandatory curriculum — including the ''answers'' to the exercises which will be made available on DTU Learn after each exercise.

=== Hand-ins ===

Regardless of your choice of writing software, the result ''' must be handed in as a PDF file'''.

It is possible (and recommended) to hand in as a group.

''The hand-ins do not affect your grade'' — they are mainly meant as a preparation for the exam. They are also a means for us to check the understanding of the teaching; if we can see that many participants have made the same mistake, we will try to explain the issue better at the beginning of the next lecture.

=== Exam ===

The exam consists of a group oral project presentation with individual questions at the end of the course, and a final 2-hour written exam. The grade is based on an overall assessment of both parts of the exam. It is a requirement that the oral presentation is completed, and the written exam is passed, to pass the entire course. The questions will be made available as a PDF file on the DTU online exam system. ''' The only accepted hand-in format is PDF'''.

All aids are allowed at the exam; you can bring any books, papers, or notes. You will have '''open access to the internet''' which includes all the materials and websites we have used during the course. You are also allowed to search for information on ChatGPT, Google, Wikipedia, etc., but you are ''not'' allowed to communicate with others through e-mail, Facebook, chat, or file-sharing websites. The internet traffic will be logged during the exam to ensure that these restrictions are kept.

Chatbots are allowed but you should state in your answer that you have used them.

=== DTU Learn Link ===
* Link to this year's DTU Learn page: https://learn.inside.dtu.dk/d2l/home/215856

=== Evaluation and feedback ===
We will be very happy to receive comments, suggestions, criticisms, or praise at any time during the semester. You can:
* send them by email to the teachers, or
* write them under "General feedback" in "Discussion" in DTU Learn.
If somebody writes a message in "Discussion", you can comment on it. If you see a message you agree with, please comment "Agree!" so that we can see that it is not just one person's opinion.

In addition, we will conduct a mid-term evaluation just after the autumn break in [https://evaluering.dtu.dk/ DTU evaluation].

== Lecture & exercise plan ==

Note: This is a ''preliminary'' plan, changes may occur!

=== Wednesday, Sep 4 — Introduction & databases ===
:'''Lectures:'''
:* ''Introduction to immunological bioinformatics'' — Carolina Barra Quaglia.
:* ''Databases'' — Carolina Barra Quaglia.
:'''Slides:''' All slides will be made available on DTU Learn.

:'''Exercise:'''


=== Wednesday, Sep 11 — B cell epitopes ===
:'''Lecture:''' ''B cell receptors and B cell epitopes'' — Carolina Barra Quaglia
:'''Slides:''' on DTU Learn.


:'''Exercise:'''


=== Wednesday, Sep 18 — Allergenicity prediction ===
:'''Lecture:''' ''Allergens'' — Carolina Barra Quglia
:'''Slides:''' on DTU Learn.

:'''Exercises:'''


=== Wednesday, Sep 25 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 1'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Oct 2 — MHC binding predictions ===
:'''Lecture:''' ''MHC binding predictions part 2'' — Morten Nielsen.

:'''Slides:''' on DTU Learn.
:'''Exercise:


=== Wednesday, Oct 9 — Antigen Processing and Immunogenicity ===

:'''Lecture:''' ''Antigen Processing'' — Carolina Barra Quaglia
:'''Lecture:''' ''Immunogenicity prediction'' — Carolina Barra Quaglia

:'''Slides:''' on DTU Learn.


:'''Exercises:'''




------
<div align="center">
'''Autumn holiday'''
</div>
------

=== Wednesday, Oct 23 — TCR interaction models and TCR repertoires ===
:'''Lecture:''' ''TCR interaction models and TCR repertoires'' — Invited Speaker (TBD)
:'''Exercise:'''


=== Wednesday, Oct 30 — Vaccine design ===
:'''Lecture:''' ''Vaccine design'' — Morten Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercise:'''


=== Wednesday, Nov 6 — Weight matrices and other prediction methods ===
:'''Lecture:''' ''Introduction to prediction methods, especially Weight Matrices'' — Henrik Nielsen
:'''Slides:''' on DTU Learn.
:'''Exercises:'''


=== Wednesday, Nov 13 — Beginning Project work ===
:'''Lecture:''' ''Short introduction to project work'' — Carolina Barra
:'''Slides:''' on DTU Learn.
:'''Exercise:''' [[ExPSIBLAST|PSI-BLAST]]

=== Wednesday, Nov 20 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Nov 27 — Project work ===
:'''Lecture:''' No LECTURE


=== Wednesday, Dec 4 — Project work poster session ===
:'''Agenda for the poster presentations:''' TBD

== Exam ==

=== Wednesday, Dec 18 ===
'''Winter exam E5-A 2024:''' Go to https://eksamen.dtu.dk/ and find 22145.