Research

From Networks to Tissue Engineering: Computational Models of Pattern Formation

Higher forms of life emerge from a more sophisticated use of often conserved signalling pathways to regulate biological function. The complex behaviour of the resulting cellular signalling networks is impossible to grasp by verbal models alone. Quantitative, computational models are required to integrate biological knowledge into a framework that permits the efficient generation of testable hypotheses and that enables an integrative understanding of biological networks.

We develop quantitative, predictive models of biological signaling networks with a view to gain a comprehensive understanding of the dynamics and evolution of cellular signaling.

All projects are carried out in close collaboration with experimental groups to ensure that quantitative data is available and that model predictions can be tested by experiments. Validated models are then used to further investigate the biological system and to address more general questions regarding the evolution and the design of cellular signaling networks.