Stochastic Reaction Diffusion Methods for Modeling Cellular Processes
November 18, 2015
3:00pm PGH 646
Abstract
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.
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