Polarization is an essential behavior of living cells, yet the dynamics of this symmetry-breaking are not fully understood. Previously, noise was thought to interfere with this process; however, we show that stochastic dynamics play an essential role in robust cell polarization and the dynamic response to changing cues. We describe a spatial stochastic model of polarisome formation in mating yeast. The model is built on simple mechanistic components, but is able to achieve a highly polarized phenotype with a relatively shallow input gradient, and to track movement in the gradient. The spatial stochastic simulations are able to reproduce experimental observations to an extent that is not possible with deterministic simulation.
Spatial stochastic simulation is a challenging computational problem. We report on our progress to date on the development of accurate and efficient algorithms and software.