Long-time analytic approximation of large stochastic oscillators: Simulation, analysis and inference.

ABSTRACT: In order to analyse large complex stochastic dynamical models such as those studied in systems biology there is currently a great need for both analytical tools and also algorithms for accurate and fast simulation and estimation. We present a new stochastic approximation of biological oscillators that addresses these needs. Our method, called phase-corrected LNA (pcLNA) overcomes the main limitations of the standard Linear Noise Approximation (LNA) to remain uniformly accurate for long times, still maintaining the speed and analytically tractability of the LNA. As part of this, we develop analytical expressions for key probability distributions and associated quantities, such as the Fisher Information Matrix and Kullback-Leibler divergence and we introduce a new approach to system-global s

SUBMITTER: Minas G 

PROVIDER: S-EPMC5555717 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature