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Courses in Practical DNA Microarray Analysis 2003

October 07 - 10 in Heidelberg

This course is already over!

Datasets and additional packages used in the practical sessions can be found here, links to the tutorial slides and assignments in the table below.

Course schedule
 Tuesday, October 07
09.00-10.30 First analysis steps Wolfgang Huber
11.00-12.30 Differential gene expression Anja von Heydebreck
13.30-14.30 First steps in R Florian Markowetz
14.45-17.00 Exercises: Exploring cDNA data Wolfgang Huber
 Wednesday, October 08
09.00-10.30 Exploratory data analysis Jörg Rahnenführer
10.30-11.30 Resampling and the bootstrap Axel Benner
11.30-12.00 Screening by ROC curve analysis Axel Benner
13.30-14.30 BioConductor Wolfgang Huber
14.45-17.00 Exercises: 2x2 factorial design Wolfgang Huber
 Thursday, October 09
09.00-10.30 Molecular Diagnosis Rainer Spang
10.30-11.30 Classification by Support Vector Machines Florian Markowetz
11.30-12.30 Model Assessment and Selection Axel Benner
13.30-17.00 Exercises: classification, model selection Florian Markowetz
Axel Benner
 Friday, October 10
09.00-11.00 Design of microarray experiments Ulrich Mansmann
11.00-12.30 Annotation Benedikt Brors
13.30-17.00 Exercises: Bootstrap Ulrich Mansmann

How to find us

We will meet on the science campus of the university of Heidelberg, "Im Neuenheimer Feld", building no. 305, room 144 (that is the seminar room in the 1st floor) on Tuesday Oct 07 at 9 am.

Here are some links that may be helpful in finding the Neuenheimer Feld in Heidelberg:
http://www.uni-heidelberg.de/univ/besucher/anfahrt.html
http://med.uni-hd.de/karte/index.html

And here is a map that should help you in finding building 305 - it is marked with a circle:
http://www.uni-heidelberg.de/univ/besucher/karten/6305.html

Bring your own data

You are encouraged to bring some of your own data to the course (e.g. genepix files or CEL/CDF). We will use this during the exercises. If you expect to have own data only later in the year, it may in fact be advantageous also to register for one the later courses in Berlin or Heidelberg.

Background Knowledge

Ideally, you are interested in mathematical and statistical problems and are familiar with at least one programming language. This course focusses on the practical side of gene expression data analysis. However, data analysis without understanding the statistical background is in general impossible. We strongly recommend you to refresh your mathematical and programming skills before attending the course.

R and Bioconductor

In the afternoon exercises you will learn how to analyze data using the statistical computing environment R [http://www.r-project.org] and BioConductor [http://www.bioconductor.org], a open source software for bioinformatics. R sources and package sources can be downloaded from The Comprehensive R Archive Network at http://cran.r-project.org. Basics are explained in Introduction to R.

Participants

Jochen Hess DKFZ Heidelberg: Signal Transduction and Growth Control
Sabine Gack DKFZ Heidelberg: Signal Transduction and Growth Control
Oliver Pein DKFZ Heidelberg: Signal Transduction and Growth Control
Bernhard Winkelmann Uniklinikum Heidelberg
Anja Victor  
Jo Vandesompele Center for medical genetics, Ghent, Belgium
Bettina Kulle Department of Genetic Epidemiology, University of Göttingen
Alexander Schramm Uniklinikum Essen
Giovanni Malerba University of Verona, Italy
Cristina Patuzzo University of Verona, Italy
Dirk Repsilber Institut für medizinische Biometrie und Statistik, Universität Lübeck
Rohit Ghai Uniklinikum Giessen
Till Soerensen 
Suse Beyer Merck Darmstadt
Michaela Kröger Merck Darmstadt
Christa Wiederkehr Swiss Institute of Bioinformatics, Basel
Johannes Schulte 

Thank you for registering! This course is fully booked and closed for registration. If you will not be able to attend, please contact Wolfgang Huber as soon as possible so that we can notify the people on the waiting list.

Further information

Please contact Dr. Wolfgang Huber: w.huber@dkfz.de

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