Mathematical Biology Seminar

Samuel Isaacson
Department of Mathematics and Statistics, Boston University

Stochastic Reaction-Diffusion Methods for Modeling Cellular Processes

Friday, December 11, 2015, at 3:05pm
LCB 219

High resolution images of cells demonstrate the highly heterogeneous nature of both the nuclear and cytosolic spaces. We are interested in understanding how this complex environment might influence the dynamics of cellular processes. To investigate this question we have worked to develop particle-based stochastic reaction-diffusion methods that can track the spatial transport and reaction of individual molecules within domains derived from imaging data.

As motivation, I will first describe some recent modeling work in which we have investigated how explicitly accounting for cellular organelles influences the time for a signal to propagate across the cytosol of cells. I will then introduce the convergent reaction-diffusion master equation (CRDME), a lattice particle-based stochastic reaction-diffusion model we are developing to allow the study of chemical pathways within such complex geometries. The CRDME is similar in spirit to the popular reaction-diffusion master equation (RDME) model. It allows for the reuse of the many extensions of the RDME developed to facilitate modeling within biologically realistic domains, while eliminating one of the major challenges in using the RDME model.