Director at the Max Planck Institute for Molecular Genetics, Berlin
We can consider life as computational processes, translating the linear information in the genome into the phenotype of the organism in a given environment. To be able to predict the effect of specific changes in these processes, in spite of their daunting complexity, would have immense practical implications, since disturbances in the complex networks involved, are likely to be the cause of most or all human diseases, with therapies acting to restore, as much as possible, the original, ‘healthy’ state. We have therefore attempted to combine tools of genetics, genomics, and systems biology to generate predictive models of the response of complex biological networks, from basic biological processes to medically important problems, combining an exhaustive characterisation of the biological system by deep sequencing and other techniques, with pathway information generated by decades of classical research, as well as by new genetic approaches. Predictive models could play an important role in improving our understanding of biology in general, but could also be a key to the development of a new individualised medicine, as well as a generation of new more targeted therapies.