Groups involved in the CoLoMoTo Consortium

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Collaborative research to develop predictive logical models of biological systems from the molecular to the community level Quantitative computational models and simulations to study cellular and molecular systems, in particular adaptation to environmental signals A repository of peer-reviewed, published, computational models Computer infrastructure and bioinformatics expertise for life sciences Apply Systems Biology approaches to biological networks involved in cancer The two groups pursue research in mathematical systems biology, particularly focusing on logical modeling of regulatory and constraint-based modeling of metabolic networks.Functional genomic data analysis and logical modelling of cellular signaling/regulatory networks involved in cell fate decisions Analysis of bacterial regulatory networks using a systems biology approach From interaction networks to cellular processes, computational modelling approaches Development of formal methods (SAT, MaxSAT, Model checking, ...) for the analysis of discrete systems (e.g. logical signalling-regulatory networks)Theoretical methods for the analysis, inference, and targeted modification of bio-molecular networks Dynamics of biological networks under diseases conditions; development of crowd-sourcing modeling approaches; computational modeling as a method to teach about biological systems.We develop methods based on logic modelling to understand the deregulation of signalling networks in disease and to identify novel therapeutics.Systems biology and multi-scale modeling of eukaryotic cell cycle regulation The Core Group Medical Systems Biology is a central facility of Ulm University for Bioinformatics and Systems Biology Apoptosis, Cancer, Immunity

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