Martin Weigt is Professor for Computational Biology at Sorbonne University in Paris, France. Being trained as a theoretical physicist, his research interests cover the interfaces between statistical physics of complex and disordered systems, computer science (combinatorial optimization, statistical and machine learning) and computational biology. Being attracted by the great amount of data emerging in biology, he develops data-driven computational and theoretical approaches in particular to biomolecular sequences. In his works, he uses the empirically observable variability between homologous protein (and RNA) sequences, to extract information about their structure and function, their interactions, their mutational landscape and their natural evolution. Besides basic insight into molecular and evolutionary mechanisms, these models allow for the generation of artificial but functional biomolecular sequences, with applications on protein optimization and design.

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