Simulation of stochastic kinetic models

Golightly, Andrew; Gillespie, Colin S.

Abstract

A growing realization of the importance of stochasticity in cell and molecular processes has stimulated the need for statistical models that incorporate intrinsic (and extrinsic) variability. In this chapter we consider stochastic kinetic models of reaction networks leading to a Markov jump process representation of a system of interest. Traditionally, the stochastic model is characterized by a chemical master equation. While the intractability of such models can preclude a direct analysis, simulation can be straightforward and may present the only practical approach to gaining insight into a system's dynamics. We review exact simulation procedures before considering some efficient approximate alternatives. © 2013 Springer Science+Business Media, LLC.

Citation

Golightly, A., & Gillespie, C. S. (2013). Simulation of stochastic kinetic models. Methods in molecular biology (Clifton, N.J. Online), 1021, 169-187. https://doi.org/10.1007/978-1-62703-450-0_9

• Journal Article Type: Article
• Online Publication Date: Apr 25, 2013
• Publication Date: Jan 1, 2013
• Deposit Date: Feb 23, 2025
• Journal: Methods in Molecular Biology
• Print ISSN: 1064-3745
• Electronic ISSN: 1940-6029
• Publisher: Humana Press
• Peer Reviewed: Peer Reviewed
• Volume: 1021
• Pages: 169-187
• DOI: https://doi.org/10.1007/978-1-62703-450-0_9
• Public URL: https://durham-repository.worktribe.com/output/3494895