Incorporating Diffusion in Complex Geometries into Stochastic Chemical Kinetics Simulations

Authors:
Samuel A. Isaacson;Charles S. Peskin
Affiliations:
-;-
Venue:
SIAM Journal on Scientific Computing
Year:
2006

Citing 0
Cited 6

Projective and coarse projective integration for problems with continuous symmetries

Journal of Computational Physics
An adaptive algorithm for simulation of stochastic reaction-diffusion processes

Journal of Computational Physics
Spatially adaptive stochastic numerical methods for intrinsic fluctuations in reaction-diffusion systems

Journal of Computational Physics
Numerical solution of linear Volterra integral equations of the second kind with sharp gradients

Journal of Computational and Applied Mathematics
Large scale agent-based modeling of the humoral and cellular immune response

ICARIS'11 Proceedings of the 10th international conference on Artificial immune systems
A First-Passage Kinetic Monte Carlo method for reaction-drift-diffusion processes

Journal of Computational Physics

Quantified Score

Hi-index	0.02

Visualization

Abstract

A method is developed for incorporating diffusion of chemicals in complex geometries into stochastic chemical kinetics simulations. Systems are modeled using the reaction-diffusion master equation, with jump rates for diffusive motion between mesh cells calculated from the discretization weights of an embedded boundary method. Since diffusive jumps between cells are treated as first order reactions, individual realizations of the stochastic process can be created by the Gillespie method. Numerical convergence results for the underlying embedded boundary method, and for the stochastic reaction-diffusion method, are presented in two dimensions. A two-dimensional model of transcription, translation, and nuclear membrane transport in eukaryotic cells is presented to demonstrate the feasibility of the method in studying cell-wide biological processes.