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Title: Hybrid stochastic simulation of reaction-diffusion systems with slow and fast dynamics

In this paper, we present a novel hybrid method to simulate discrete stochastic reaction-diffusion models arising in biochemical signaling pathways. We study moderately stiff systems, for which we can partition each reaction or diffusion channel into either a slow or fast subset, based on its propensity. Numerical approaches missing this distinction are often limited with respect to computational run time or approximation quality. We design an approximate scheme that remedies these pitfalls by using a new blending strategy of the well-established inhomogeneous stochastic simulation algorithm and the tau-leaping simulation method. The advantages of our hybrid simulation algorithm are demonstrated on three benchmarking systems, with special focus on approximation accuracy and efficiency.
Authors:
;  [1]
  1. Department of Mathematics, Ryerson University, Toronto, Ontario M5B 2K3 (Canada)
Publication Date:
OSTI Identifier:
22493341
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Chemical Physics; Journal Volume: 143; Journal Issue: 23; Other Information: (c) 2015 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL CHEMISTRY; ACCURACY; ALGORITHMS; BENCHMARKS; CHEMICAL REACTIONS; COMPUTERIZED SIMULATION; DIFFUSION; EFFICIENCY; HYBRIDIZATION; PARTITION; STOCHASTIC PROCESSES