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Author Wu, Fuke ♦ Tian, Tianhai ♦ Rawlings, James B. ♦ Yin, George
Source United States Department of Energy Office of Scientific and Technical Information
Content type Text
Language English
Subject Keyword INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL CHEMISTRY ♦ ALGORITHMS ♦ COMPUTERIZED SIMULATION ♦ EXPERIMENTAL DATA ♦ KINETICS ♦ LANGEVIN EQUATION ♦ STOCHASTIC PROCESSES
Abstract The frequently used reduction technique is based on the chemical master equation for stochastic chemical kinetics with two-time scales, which yields the modified stochastic simulation algorithm (SSA). For the chemical reaction processes involving a large number of molecular species and reactions, the collection of slow reactions may still include a large number of molecular species and reactions. Consequently, the SSA is still computationally expensive. Because the chemical Langevin equations (CLEs) can effectively work for a large number of molecular species and reactions, this paper develops a reduction method based on the CLE by the stochastic averaging principle developed in the work of Khasminskii and Yin [SIAM J. Appl. Math. 56, 1766–1793 (1996); ibid. 56, 1794–1819 (1996)] to average out the fast-reacting variables. This reduction method leads to a limit averaging system, which is an approximation of the slow reactions. Because in the stochastic chemical kinetics, the CLE is seen as the approximation of the SSA, the limit averaging system can be treated as the approximation of the slow reactions. As an application, we examine the reduction of computation complexity for the gene regulatory networks with two-time scales driven by intrinsic noise. For linear and nonlinear protein production functions, the simulations show that the sample average (expectation) of the limit averaging system is close to that of the slow-reaction process based on the SSA. It demonstrates that the limit averaging system is an efficient approximation of the slow-reaction process in the sense of the weak convergence.
ISSN 00219606
Educational Use Research
Learning Resource Type Article
Publisher Date 2016-05-07
Publisher Place United States
Journal Journal of Chemical Physics
Volume Number 144
Issue Number 17


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