Computational Biology Division

The mission of the group is to enable a "Systems" approach for gene function analysis. A Systems Biology approach hinges on the capability to produce, manage, mine and model large volumes of (functional genomics) data, and to be able to derive new hypotheses about the function of genes and networks. The group is exploring different approaches to allow the modeling of time-series data and of large, compendium-type microarray datasets, and to integrate these data with other types of data (phenotype, protein features, GO). Another major effort of the group is on 'knowledge management': through the integration and development of ontologies we build a knowledge framework that is able to combine data from public databases and scientific literature that we can exploit for querying and computational reasoning. Today we are focusing on three main topics that are biologically closely connected: Cell Cycle Control, Leaf Development, and Heterosis / Biomass Production. We team up with the subsequent 'wet-lab' research groups in our department. The aim of our research is two-fold: to identify novel genes involved in these biological processes, and to develop functional models that provide qualitative description with predictive power. These models thus can be seen as 'hypothesis-generating engines' that drive wet-lab experiments to provide additional data.