Autumn2023: Difference between revisions

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

Revision as of 15:47, 5 March 2024

Course 22140 - plan for autumn 2023

Teachers:

  • Lars Rønn Olsen (course organizer) - contact: lronn@dtu.dk
  • Kristoffer Vitting-Seerup (course organizer) - contact: krivi@dtu.dk
  • Rasmus Wernersson (external lecturer) - contact: rawe@dtu.dk
  • Hanxi Li (teaching assistant) - contact: hanxli@dtu.dk


DTU Learn


Bioinformatics

Besides knowledge about basic molecular biology and biochemistry, a prerequisite for this course is bioinformatics (usually from course 22211 or one of its variants). If you need to read up on some bioinformatics topics, please use the links below.


R

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

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

Weekly assignments

As part of the computer exercises you (or your group) should keep a "log book" and answer the questions/report observations as you work though the exercise. The parts you need to document will be marked with the small "report icon" also seen here.

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

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

Allowed formats:

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


Lecture plan, autumn 2023

When and Where

  • When: Each Thursday from 13:00-17:00
  • Where: Building 303A auditorium/group-room 045


Block #1: Introduction

Responsible for this block: Lars Rønn Olsen and Rasmus Wernersson

Lecture 01 (August 31) - Intro 1

Lecture: Introduction to Systems Biology and biological networks - Rasmus Wernersson.
Slides: Will be uploaded to DTU Learn
Readings: Can a Biologist fix a radio? - Lazebnik Y., Cancer Cell 2002 (PDF)
Exercise: Introduction to working with networks in R - Answers: Exercise #1 answers

Lecture 02 (Sep 7) - Intro 2

Lecture: Protein-protein interaction networks. Experimental methods and interpretation. - Lars Rønn Olsen
Slides: To appear on DTU Learn
Hand-outs: SnapShot: Protein-Protein Interaction Networks - Seebacher & Gavin, Nature 2011 (PDF) - focus on the EXPERIMENTAL METHODS part for this week.
Readings:
  • Lecture note on quality scoring of protein-protein interaction data, notes and examples (PDF)
  • Comparative assessment of large-scale data sets of protein-protein interactions - von Mering C, et al. Nature 2002 (PDF)
Exercise:

Lecture 03 (Sep 14) - Intro 3

Lecture: Network topology - Lars Rønn Olsen
Slides: On DTU Learn.
Hand-outs: SnapShot: Protein-Protein Interaction Networks - (SAME AS LAST WEEK) (PDF) - read the rest for this week.
Readings: Global network properties. Barabasi& Oltvai, Nat Rev Genet 2004 (PDF) - concentrate on Box 1 and Box 2.
Exercises:
  1. Handout exercise: Network topology exercise (PDF)
  2. Computer exercise: Topology/statistics/modules Network topology and statistics - Answers: Answers to igraph exercise

Block #2: Case: Yeast systems biology

Responsible for this block: Rasmus Wernersson and Kristoffer Vitting-Seerup

Lecture 04 (Sep 21) - Yeast Systems Biology 1

Lecture: Yeast Cell Cycle introduction - Rasmus Wernersson.
Slides: Will be uploaded to DTU Learn
Readings:
  • Background on budding yeast cell cycle and cell cycle regulation (PDF).
  • Source: http://mpf.biol.vt.edu/research/budding_yeast_model/pp/index.php (much more information about modelling the yeast cell cycle can be found here) [NOT part of the curriculum].
  • Important: You don't need to understand all the finer points about the regulation, but make sure you known the phases of the cell cycle.
Saccharomyces Genome Database: http://www.yeastgenome.org/
Exercise: Yeast cell cycle 1 - introduction to data and methods - Answers: Yeast 1 answers

Lecture 05 (Sept 28) - Yeast Systems Biology 2

Lecture: Gene Ontology and large scale data analysis - Rasmus Wernersson
Readings: Two introductory papers to The Gene Ontology (GO). Choose the one you prefer.
  • Intro for bioinformaticians: The what, where, how and why of gene ontology - a primer for bioinformaticians - PDF (NEW LINK) (focus on the first three pages).
    • Focuses mostly on the structure of the GO, the evidence behind the annotations and relations of the genes/proteins to the categories.
  • Intro for biologists: Gene Ontology: tool for the unification of biology - PDF (NEW LINK)
    • Describes more the general idea behind GO and why it is useful.
Slides: On DTU Learn
Exercise: Gene Ontology - yeast cell cycle examples - Answers: answers

Lecture 06 (Oct 5) - Yeast Systems Biology 3

Lecture: Introduction to transcriptomics - Kristoffer Vitting-Seerup
Readings: A brief introduction to DNA micro-arrays (DTU Learn) - Rasmus Wernersson
Background: (Optional) - If you need a reminder about how the Log2 function works, then have a look at Appendix A in Thomas Schneider's Information Theory Primer (PDF)
Slides: To appear on DTU Learn
Exercise: Yeast cell cycle: single point arrest DNA microarray studies - Answers: Answers

Lecture 07 (Oct 12) - Yeast Systems Biology 4

Lecture: How proteins collaborate during the phases of cell devision - Rasmus Wernersson.
Readings: Cyclebase paper - (skim it - make sure to understand Fig 1).
Slides: To appear on DTU Learn
Exercise: Mapping temporal expression data onto networks Answers: answers

Autumn vacation (Week 42)

Block #3: Case: Human disease biology

Responsible for this block: Lars Rønn Olsen, Rasmus Wernersson, and Kristoffer Vitting-Seerup

Lecture 08 (Oct 26) - Systems Biology in Biomedical Research (Heart diseases) 1 - CANCELLED

Lecture 09 (Nov 2) - Systems Biology in Biomedical Research (Heart diseases) 2

Lecture: Virtual pulldown and protein complex detection - Lars Rønn Olsen and Giorgia Moranzoni
Readings:
Extra: (not curriculum)
Exercises: DiscoNet - Answers: DiscoNet answers


Lecture 10 (Nov 9) - Integrating multiple omics data types for cancer research

Lecture: Systems Biology in Cancer - Kristoffer Vitting-Seerup
Readings:
  • The Hallmarks of Cancer, Hanahan & Weinberg 2011 (Article link)
Slides: On DTU Learn
Exercises: Multiomics data integration Answers: answers


Lecture 11 (Nov 16) - Essential R functions + exam exercise

Lecture: Week 10 (and to some extent week 9) exercise walk-through
Slides: To appear on DTU Learn
Exercise: Old exam set (adapted to R)


Lecture 12 (Nov 23) - QnA / AMA

Lecture: Kristoffer Vitting-Seerup
Topics: Anything you would like to a refresher about


Lecture 13 (Nov 30) - Systems Biology in Biomedical Research 3 (ZS Revelen framework, drug targets)

Lecture: Biomarker and drug target identification - Rasmus Wernersson.
Readings:
  • Systems biology investigation of COVID-19: Network analysis of COVID19 – Intomics (PDF on DTU Learn)
  • It's a document with a written explanation of the COVID-19 analysis. (PDF of Intomics web-page, apologies for the sub-optimal formatting)
  • Please read all of it - including methods. It is written for a non-technical audience and should be easy to understand.
Slides: To appear on DTU Learn
Exercise:
  • PDF on Learn
Link to ZS Revelen: https://zs-revelen.com/
  • Please register your email with ZS Revelen before the exercise. Please use your DTU email.


Old exam sets

  • On Learn


Exam

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