Stiffness detection and reduction in discrete stochastic simulation of biochemical systems

Authors:
Yang Pu;Layne T. Watson;Yang Cao
Affiliations:
Virginia Polytechnic Institute and State University, Blacksburg, VA;Virginia Polytechnic Institute and State University, Blacksburg, VA;Virginia Polytechnic Institute and State University, Blacksburg, VA
Venue:
SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
Year:
2010

Citing 2
Cited 0

Computer Methods for Ordinary Differential Equations and Differential-Algebraic Equations

Computer Methods for Ordinary Differential Equations and Differential-Algebraic Equations
Multiscale stochastic simulation algorithm with stochastic partial equilibrium assumption for chemically reacting systems

Journal of Computational Physics

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Abstract

Typical multiscale biochemical models contain fast-scale and slow-scale reactions, where "fast" reactions fire much more frequently than "slow" ones. This feature often causes stiffness in discrete stochastic simulation methods such as Gillespie's algorithm and tau-leaping methods leading to inefficient simulation. This paper proposes a new strategy to automatically detect stiffness and identify species that cause stiffness. Stiffness reduction methods are also discussed. Numerical results on a heat shock protein regulation model demonstrate the efficiency and accuracy of the proposed method for multiscale biochemical systems.