Projects: MPI-CBG - zechner

Our theoretical focus lies in the mathematical and computational analysis of stochastic biological processes. We develop theory to (a) effectively approximate and simulate stochastic biological networks, (b) infer their biophysical parameters from single-cell experimental data (c) and analyze them in terms of information flow and feedback control. Recently, we have been putting special emphasis on approaches that can bridge between different scales of biological organization (e.g., molecules, compartments, cells). In this project, we study the role of biomolecular condensates to control intracellular noise. We have recently provided a first proof-of-principle of this idea, showing that protein concentration noise can be strongly reduced when the protein partitions into condensates. Based on these findings we are now exploring the generality of this concept in the context of cellular information processing and feedback control. To this end, we merge statistical physics with control theo

Our theoretical focus lies in the mathematical and computational analysis of stochastic biological processes. We develop theory to (a) effectively approximate and simulate stochastic biological networks, (b) infer their biophysical parameters from single-cell experimental data (c) and analyze them in terms of information flow and feedback control. Recently, we have been putting special emphasis on approaches that can bridge between different scales of biological organization (e.g., molecules, compartments, cells). In this project, we study the role of biomolecular condensates to control intrac