What do we do?
Our main research interest at the Genome Systems Biology (GSB) Group is the study of genome-wide regulatory systems in order to reconstruct them from high-throughput molecular data, understand and model how they have evolved, and search for design principles in their construction. In particular, we are 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.
The main highlight in 2015 was the publication of the first major work from our group’s wet lab in which we uncovered a general mechanism for the de novo evolution of gene regulation, and found that gene expression noise plays a crucial role in facilitating its evolution.
A second major highlight involves Crunch – a completely automated webserver for ChIP-seq analysis – which went online at crunch.unibas.ch as part of the group’s SwissRegulon portal. Crunch performs all steps of the ChIP-seq analysis, from raw data quality control, read mapping, fragment-size estimation, peak detection, and peak annotation to novel DNA sequence motif analysis. In particular, Crunch finds a complementary set of motifs that can explain the ChIP-seq data, and then comprehensively characterizes the occurrence of these motifs across the ChIP binding peaks.
Main publications 2015
- Pemberton-Ross PJ et al. ARMADA: Using motif activity dynamics to infer gene regulatory networks from gene expression data. Methods 2015;85:62-74.
- Schertel C et al. A large-scale, in vivo transcription factor screen defines bivalent chromatin as a key property of regulatory factors mediating Drosophila wing development. Genome Res 2015;25(4):514-23.
- Wolf L et al. Expression noise facilitates the evolution of gene regulation. eLife 2015;4:e05856.