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	Lecture Series, Talks and Events
		B-IT hosts 2nd International Symposium in Media Informatics
		B-IT Tutorial on Robotics
		B-IT Hosts Workshop On Successful EU-funded Project WISDOM ON December 16, 2005
		B-IT activities grow: Schüler-Krypto 2006
		B-IT hosts Informatiktage
		Erstes B-IT Wirtschaftsforum am 16.9.2003
		B-IT hosts the CoreGRID Summer School 2006
		First B-IT Summer School on Crpytography
		Personal Orchestra
		B-IT Life Science Informatics Lecture Series 2008
		B-IT Life Science Informatics Lecture Series 2009
		Talk by Professor Steve Horvath
		Second B-IT Economic Forum - 2. B-IT Wirtschaftsforum
		B-IT Life Science Informatics Lecture Series 2010
		Lecture Series "Algorithms in Bioinformatics"
		B-IT Lecture Series in Life Science Informatics 2011
		Lecture Series "Algorithms in Bioinformatics"
		Talk by Professor Prof Dr. Heinz-Juergen Steinhoff, UNiversity of Osnabrück, Germany
		B-IT Lecture Series in Life Science Informatics 2012
		B-IT Lecture Series: Statistical and Algorithmic Bioinformatics Winter Semester 2012/2013

	B-IT Annual Report

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B-IT Universities Institute

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	Master Programme of Life Science Informatics

	Master Programme of Media Informatics

	Application for Master Programmes

	International Program of Excellence (IPEC)

B-IT Applied Science Institute

	Master Programme of Autonomous Systems

Abstract to "Model-based Gene Set Enrichment Analysis" by Dr. Julien Gagneur

The interpretation of data-driven experiments in genomics often involves a search for biological categories that are enriched for the responder genes identified by the experiments. However, knowledge bases such as the Gene Ontology (GO) contain hundreds or thousands of categories with very high overlap between categories. Thus, enrichment analysis performed on one category at a time frequently returns large numbers of correlated categories, leaving the choice of the most relevant ones to the user’s interpretation.

I will present Model-based Gene Set Analysis (Bauer et al. NAR, 2010) in which we tackle the problem by turning the question differently. Instead of searching for all significantly enriched groups, we search for a minimal set of groups that can explain the data. We model the experimental observation by a set of "active" groups. Our model penalizes the number of active groups thus naturally providing parsimonious solutions. Application to a gene expression data set in yeast demonstrates that the method provides high-level, summarized views of core biological processes and correctly eliminates confounding associations.

NEWS

B-IT hosts Informatiktage 2013
Special Courses for Excellent Graduate and Doctoral Students held in B-IT, March 22-23, 2013 [more]

Matthias Jarke Appointed to CONNECT Advisory Forum
[more]

Two Honors for Professor Matthias Jarke
[more]

NRW Young Scientist Award for Nenad Biresev
[more]

The ABC of Life Science Informatics
Mini-Symposium of Bioinformatics and Chemoinformatics Research Groups from the Aachen-Bonn-Cologne Region on December 14, 2012 [more]