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2013•Scholarworks@UNIST (Ulsan National Institute of Science and Technology)Open access

A Moment Closure Method for Stochastic Chemical Reaction Networks with General Kinetics

Chang Hyeong Lee

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Abstract

The moment closure method is an approximation method for describing the stochastic dynamics of chemical reaction networks. In this paper we develop a moment closure method for stochastically modeled chemical reaction networks with general reaction rate laws including mass action, rational and fractional rate laws. Based on the Taylor formula of the reaction rate functions and truncation at a certain order of moment, we find a closed system of equations for the moments. We show the accuracy and efficiency of the method by comparing the simulation results of motivating examples obtained by the moment closure method and the stochastic simulation algorithm.

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What this paper is about

The moment closure method is an approximation method for describing the stochastic dynamics of chemical reaction networks. In this paper we develop a moment closure method for stochastically modeled chemical reaction networks with general reaction rate laws including mass action, rational and fractional rate laws. Based on the Taylor formula of the reaction rate functions and truncation at a certain order of moment, we find a closed system of equations for the moments. We show the accuracy and efficiency of the method by comparing the simulation results of motivating examples obtained by the moment closure method and the stochastic simulation algorithm.

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Available abstract

The moment closure method is an approximation method for describing the stochastic dynamics of chemical reaction networks. In this paper we develop a moment closure method for stochastically modeled chemical reaction networks with general reaction rate laws including mass action, rational and fractional rate laws. Based on the Taylor formula of the reaction rate functions and truncation at a certain order of moment, we find a closed system of equations for the moments. We show the accuracy and efficiency of the method by comparing the simulation results of motivating examples obtained by the moment closure method and the stochastic simulation algorithm.

Key concepts: Moment closure, Closure (psychology), Moment (physics), Truncation (statistics), Mathematics, Applied mathematics, Rate equation, Chemical kinetics

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