ABSTRACT

Cellular processes are complex and involve many components whose interactions are stochastic and only partially characterized. Instead of guessing unknown details, our work focuses on analyzing classes of biochemical reaction networks that share some features but are left to vary arbitrarily in all unknown features. This allows us to derive general impossibility constraints to guide the design of synthetic cellular circuits and understand the operating principles of naturally occurring processes. For example, our work showed that feedback control in cells must involve at least one “sacrificial” component with increased fluctuations to suppress fluctuations in other components. Furthermore, we demonstrated how fluctuations constraints can be exploited to detect causal effects in complex gene regulatory networks.

BIOSKETCH

UG (Mathematics): Imperial College London and Cambridge University.
PhD: Max-Planck-Institute for the Physics of Complex Systems, Dresden (in close collaboration with MPI for Cell Biology & Genetics)
Postdoc: Harvard Medical School (Dept. of Systems Biology)
Faculty since 2017: University of Toronto (Dept. of Physics)