301. D-leaping: Accelerating stochastic simulation algorithms for reactions with delays
- Author
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Basil Bayati, Philippe Chatelain, Petros Koumoutsakos, University of Zurich, and Koumoutsakos, P
- Subjects
Mathematical optimization ,Work (thermodynamics) ,Physics and Astronomy (miscellaneous) ,Differential equation ,SX20 Research, Technology and Development Projects ,leaping ,SX00 SystemsX.ch ,2604 Applied Mathematics ,SX15 WingX ,Stochastic simulation ,1706 Computer Science Applications ,3101 Physics and Astronomy (miscellaneous) ,Tau-leaping ,2612 Numerical Analysis ,Mathematics ,Numerical Analysis ,Stochastic process ,Applied Mathematics ,Delay differential equation ,3100 General Physics and Astronomy ,Delayed reactions ,Computer Science Applications ,Computational Mathematics ,Orders of magnitude (time) ,Modeling and Simulation ,Benchmark (computing) ,570 Life sciences ,biology ,Tau ,Algorithm ,2605 Computational Mathematics ,2611 Modeling and Simulation - Abstract
We propose a novel, accelerated algorithm for the approximate stochastic simulation of biochemical systems with delays. The present work extends existing accelerated algorithms by distributing, in a time adaptive fashion, the delayed reactions so as to minimize the computational effort while preserving their accuracy. The accuracy of the present algorithm is assessed by comparing its results to those of the corresponding delay differential equations for a representative biochemical system. In addition, the fluctuations produced from the present algorithm are comparable to those from an exact stochastic simulation with delays. The algorithm is used to simulate biochemical systems that model oscillatory gene expression. The results indicate that the present algorithm is competitive with existing works for several benchmark problems while it is orders of magnitude faster for certain systems of biochemical reactions.
- Published
- 2009