Inference for Stochastic Chemical Kinetics Using Moment Equations and System Size Expansion.

ABSTRACT: Quantitative mechanistic models are valuable tools for disentangling biochemical pathways and for achieving a comprehensive understanding of biological systems. However, to be quantitative the parameters of these models have to be estimated from experimental data. In the presence of significant stochastic fluctuations this is a challenging task as stochastic simulations are usually too time-consuming and a macroscopic description using reaction rate equations (RREs) is no longer accurate. In this manuscript, we therefore consider moment-closure approximation (MA) and the system size expansion (SSE), which approximate the statistical moments of stochastic processes and tend to be more precise than macroscopic descriptions. We introduce gradient-based parameter optimization methods and uncer

SUBMITTER: Frohlich F 

PROVIDER: S-EPMC4957800 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature