Our Research Mission
How do cells and tissues process noisy information and robustly self-organize into functional structures? How do local interactions at small scales give rise to emergent dynamics and self-organized spatio-temporal patterns at large scales in living matter – despite noise, variations, and an ever-fluctuating environment?
The Biological Algorithms Group wants to understand the nonlinear dynamics of biological systems and the underlying mechanisms of feedback control. Biological systems of interest include the dynamics of cilia, cellular navigation, and pattern formation during embryonic development and regeneration – e.g. how muscle cells form crystal-like myofibrils, diatom cells build their intricate glass shells, and axolotl regrow lost limbs of correct size. We use tools from nonlinear dynamics, stochastic processes, statistical physics and information theory in close collaboration with biologists. We aim at quantitative theoretical descriptions of biological dynamics in cells and tissues, calibrated by experimental data and allowing for testable predictions, to decipher algorithms of life.