A Critical Comparison of Rejection-Based Algorithms for Simulation of Large Biochemical Reaction Networks

Research output: Contribution to journalArticleScientificpeer-review


Research units

  • University of Trento


The rejection-based simulation technique has been applying to improve the computational efficiency of the stochastic simulation algorithm (SSA) in simulating large reaction networks, which are required for a thorough understanding of biological systems. We compare two recently proposed simulation methods, namely the composition–rejection algorithm (SSA-CR) and the rejection-based SSA (RSSA), aiming for this purpose. We discuss the right interpretation of the rejection-based technique used in these algorithms in order to make an informed choice when dealing with different aspects of biochemical networks. We provide the theoretical analysis as well as the detailed runtime comparison of these algorithms on concrete biological models. We highlight important factors that are omitted in previous analysis of these algorithms. The numerical comparison shows that for reaction networks where the search cost is expensive then SSA-CR is more efficient, and for reaction networks where the update cost is dominant, often the case in practice, then RSSA should be the choice.


Original languageEnglish
Pages (from-to)3053-3073
Number of pages21
JournalBulletin of Mathematical Biology
Issue number8
Early online date6 Jul 2018
Publication statusPublished - 1 Aug 2019
MoE publication typeA1 Journal article-refereed

    Research areas

  • Computational biology, Rejection-based simulation technique, Stochastic simulation

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