Bioinformatics II

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Contents

Overview

During this 4 week bioinformatics programme the participants acquire fundamental skills in statistics, computer programming, and using public databases 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 can choose to attend parts of this course.

  • Location: Academic Medical Center, Amsterdam
  • Date: 30 March - 24 April 2009
  • Max participants: 20
  • Costs: Free
  • Course material: All course material is provided during the course.
  • ECTS: 6
  • Coordinator: Perry Moerland
  • Documents: Schedule 2009 
Registration
1. Send an email with contact details to Els Natzijl-Visser
2. Indicate whether you are a master student, PhD student, post-doc, or something else.
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 some basic knowledge in biology, bioinformatics, statistics, the 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.

Recommended reading:

  • Molecular Biology of the Cell. B. Alberts (Ed.) Garland Publishing Inc,US.
  • Essential Bioinformatics. Jin Xiong (Ed.) Cambridge University Press.

Coordinator: Perry Moerland

  • Introduction cell biology (background material)
  • March 30: Introduction bioinformatics
  • March 30-31: Introduction statistics
  • April 2: Introduction microarrays
  • April 2: Clustering
  • April 3: Classification & Regression(Part 1)
  • April 3: Classification & Regression (Part 2)
  • April 3: Introduction pathway analysis

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 and Affymetrix), 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 http://www.bioconductor.org/pub/docs/mogr/

Recommended reading:

Coordinator: Perry Moerland


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. 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 http://www.bioconductor.org/pub/docs/mogr/

Coordinator: Perry Moerland

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