A scalable moment-closure approximation for large-scale biochemical reaction networks.

ABSTRACT:

Motivation

Stochastic molecular processes are a leading cause of cell-to-cell variability. Their dynamics are often described by continuous-time discrete-state Markov chains and simulated using stochastic simulation algorithms. As these stochastic simulations are computationally demanding, ordinary differential equation models for the dynamics of the statistical moments have been developed. The number of state variables of these approximating models, however, grows at least quadratically with the number of biochemical species. This limits their application to small- and medium-sized processes.

Results

In this article, we present a scalable moment-closure approximation (sMA) for the simulation of statistical moments of large-scale stochastic processes. The sMA exploits the st

SUBMITTER: Kazeroonian A 

PROVIDER: S-EPMC5870627 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature