# 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.