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Bioinformatics-II: Analysis of genome-wide expression data

During this 4 week bioinformatics programme the participants acquire fundamental skills in data analysis, microarray analysis, and programming and apply these skills to real-life bioinformatics problems. This course is part of the bioinformatics track of the GRID computing master at the UvA. Other participants are welcome to attend (parts of) this course.

  • Location: Academic Medical Center, Amsterdam. See here how to get there.
  • Max participants: 20
  • Costs: Free
  • Course material: All course material is provided during the course.
  • ECTS: 6 (module 1: 1 ECTS, module 2: 2 ECTS, module 3: 3 ECTS)
  • Coordinator: Perry Moerland

  1. Registration for 2011 is closed
  2. Indicate whether you are a master student, PhD student, post-doc, ....
  3. Indicate which modules you want to attend. See the module description for other information you need to provide.

Note: This course focuses on the analysis of microarray data. This part of the programme 'bioinformatics' doesn't consider any aspect of GRID (computing).

Module 1 - Introduction

In this first module the students are given the opportunity to acquire basic knowledge in biology, bioinformatics, statistics, analysis of microarrays, and biological pathways. Depending on his/her background the student may choose to skip certain topics of this module. Please indicate which lectures you will attend when you register for this module. The participants will get a certificate listing the topics that were attended.

Literature: The student will receive handouts during the lectures. Slides will in general be made available on the wiki right after the lecture.

Coordinator: Perry Moerland


Introduction to Biology

Recommended reading
  • Molecular Biology of the Cell. B. Alberts (Ed.) Garland Publishing Inc,US.
  • Slides with an introduction to cell biology

Introduction to Bioinformatics

Recommended reading
  • Essential Bioinformatics. Jin Xiong (Ed.) Cambridge University Press.

Introduction to statistics

Recommended reading
  • Altman, DG (1999) Practical statistics for medical research. Chapman & Hall/CRC, Boca Raton

Background information

Module 2 - R/Bioconductor

Much of data analysis in bioinformatics is done within the R/Bioconductor statistical environment. For example, many statistical methods for the analysis of microarray and other high-throughput data are available from Bioconductor. In this module you will get acquainted with R/Bioconductor and will learn to apply a range of statistical techniques to microarray data. The main topics include microarray analysis (2-dye spotted, Agilent, Affymetrix, Illumina), linear models, unsupervised and supervised learning, and the use of meta-data. Participants will get a certificate if they successfully carry out the computer exercises. Some programming experience is a plus for this module.

Literature: During the course you will receive handouts from Bioinformatics and Computational Biology Solutions Using R and Bioconductor Gentleman, R.; Carey, V.; Huber, W.; Irizarry, R.; Dudoit, S. (Eds.), Springer, 2005

Recommended reading

Coordinator: Perry Moerland


Here is how to log in on a PC in the exercise rooms (L-007):
  • username PC: bioinfo
  • password: ask Perry
  • group: common4

All exercises will be done with a student account on our UNIX server at SARA. To work on SARA you need to start PuTTY ("Geneeskunde - Bio Informatica - PuTTY") . You will have to enable X11 from PuTTY before connecting to the server. When opening PuTTY, in the configuration window go to "Connection-SSH-X11" and select "Enable X11 forwarding".

  • host name:
  • login as: you can find your username here
  • password: ask Perry

To forward plots from SARA to your PC, you'll need to start Exceed ("MIK - Hummingbird Connectivity 10 - Exceed - Exceed"). When working on your own laptop/PC, you can install the free Xming to enable X11 forwarding to your PC. For transfering files between PC and SARA you can use WinSCP ("MIK - WinSCP - WinSCP"). For editing R files you can use ConTEXT ("MIK - ConTEXT - ConTEXT").


Module 3 - Analysis of microarray data and pathway analysis

In this module you will apply what was learnt in the Bioconductor module (module 2) to a challenging microarray experiment from a recent Nature paper. You will analyze the activation status of several human oncogenic pathways. You will validate the signatures found in tumor samples derived from various mouse cancer models. Association with disease outcome of the oncogenic pathway signatures will be validated for various publicly available human cancer datasets. PhD students and post-docs can use this module to bring along their own dataset and try to analyze it using the tools learnt in the first three weeks. Good knowledge of R and several Bioconductor packages is required (therefore it is compulsory that you attend module 2). Participants will get a certificate if they successfully write a short report on their analysis efforts.

Literature: During the course you will receive handouts from Bioinformatics and Computational Biology Solutions Using R and Bioconductor Gentleman, R.; Carey, V.; Huber, W.; Irizarry, R.; Dudoit, S. (Eds.), Springer, 2005

Coordinator: Perry Moerland

Topic revision: r29 - 27 May 2020, UnknownUser Search
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