Groups - Basel - Genome Systems Biology - E. Van Nimwegen
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Erik van Nimwegen


The main research interest of the Genome Systems Biology (GSB) group is the study of genome-wide regulatory systems, to reconstruct them from high-throughput molecular data, to understand and model how they have evolved, and to search for design principles in their construction. In particular, the GSB group is developing and applying new algorithmic tools for the automated reconstruction of genome-wide regulatory networks from comparative genomic, deep sequencing, and other high-throughput data. In addition, methods are being developed for studying genome evolution and the evolution of regulatory networks in particular.



Given the enormous variety of animal cells across different tissues and organs, it is easy to forget that all cells of an organism share a common “blueprint”, i.e. a common genome.
We now know that the major determinant of a cell’s state is the expression pattern of its genes which is controlled by regulatory genes. They bind to short sequence patterns in the DNA and, in this way, “read out” the regulatory programs encoded in the genome. In contrast to the large genes that encode proteins, the small regulatory sequences that control gene expression are generally hard to find. Moreover, little is known about their functioning. Our group develops mathematical and computational methods for deciphering this “regulatory code” in the DNA, and for modeling how constellations of regulatory sequences control gene expression.

Projects and Services

Our group provides a number of online services and database associated with the gene regulatory networks through our SwissRegulon website. First of all, our group has developed a number of algorithms for the discovery of regulatory motifs and the genome-wide annotation of regulatory sites based on high-throughput data.
For example, our PhyloGibbs algorithm integrates the search for over-represented sequence motifs with comparative genomic analysis of sequence conservation patterns within a rigorous Bayesian probabilistic frame work. In addition to distributing the PhyloGibbs source code, PhyloGibbs is also provided on a Web server that allows users to discover regulatory motifs in their own sequences. Similarly, MotEvo is a state-of-the-art algorithm for genome-wide transcription factor binding site prediction that is made available through SwissRegulon.

In addition, we provide genome-wide annotation of regulatory sites for a large number of transcription factors across a range of model organisms including human, mouse, yeast, and E. coli both through a genome-browser and in downloadable form.

Through a collaboration with the Omics Science Center at Riken, Yokohama, we also provide comprehensive genome-wide annotations of promoter regions in human and mouse.

Finally, beyond annotation regulatory sites and regions on the genomes of model organisms, SwissRegulon now also provides automated tools for analyzing gene expression and ChIP-seq data-sets in terms of the predicted regulatory sites. In particular, MARA (Motif Activity Response Analysis) is a fully-automated web-service that takes gene expression or ChIP-seq data-sets as input and predicts the key transcription factors involved in the regulation, their sample dependent activities, and their genome-wide target genes. MARA allows users to reconstruct transcription regulatory networks for any model system of interest ab initio.

Websites for Further Information

Genome Systems Biology Group:




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