Scientific Computing in Molecular Biology
Frank Noe, Free University of Berlin

Abstract: The application field of molecular biology has long resisted mathematics and in particular classical scientific computing due to a number of key problems: (1) extremely high dimensionality, (2) extremely large span of relevant timescales, and (3) inherent stochasticity. About 10 years ago, the transfer  operator approach has been introduced which has allowed to reformulate molecular dynamics in a way that provides (1) a relatively low effective dimensionality, (2) only maintains the (interesting) slow timescales, and (3) describes the deterministic transport properties of the system. This approach allows scientific computing approaches such as error control and adaptive refinement to be used to solve the molecular kinetics even in cases where a direct simulation would be computationally unfeasible. In this talk I will describe the transfer operator technique and illustrate its usefulness to modeling the kinetics of complex molecular systems and understanding the relation between microscopic (computational) and macroscopic (experimental) observables.