HRSSA - Efficient hybrid stochastic simulation for spatially homogeneous biochemical reaction networks

Luca Marchetti*, Corrado Priami, Vo Hong Thanh

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

21 Citations (Scopus)

Abstract

This paper introduces HRSSA (Hybrid Rejection-based Stochastic Simulation Algorithm), a new efficient hybrid stochastic simulation algorithm for spatially homogeneous biochemical reaction networks. HRSSA is built on top of RSSA, an exact stochastic simulation algorithm which relies on propensity bounds to select next reaction firings and to reduce the average number of reaction propensity updates needed during the simulation. HRSSA exploits the computational advantage of propensity bounds to manage time-varying transition propensities and to apply dynamic partitioning of reactions, which constitute the two most significant bottlenecks of hybrid simulation. A comprehensive set of simulation benchmarks is provided for evaluating performance and accuracy of HRSSA against other state of the art algorithms.

Original languageEnglish
Pages (from-to)301-317
Number of pages17
JournalJournal of Computational Physics
Volume317
DOIs
Publication statusPublished - 2016
MoE publication typeA1 Journal article-refereed

Keywords

  • Biochemical reaction networks
  • Hybrid simulation
  • Stochastic simulation
  • Systems biology

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