S-Leaping: An Adaptive, Accelerated Stochastic Simulation Algorithm, Bridging τ-Leaping and R-Leaping

We propose the S -leaping algorithm for the acceleration of Gillespie’s stochastic simulation algorithm that combines the advantages of the two main accelerated methods; the τ -leaping and R -leaping algorithms. These algorithms are known to be efficient under different conditions; the τ -leaping is...

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Vydáno v:	Bulletin of mathematical biology Ročník 81; číslo 8; s. 3074 - 3096
Hlavní autoři:	Lipková, Jana, Arampatzis, Georgios, Chatelain, Philippe, Menze, Bjoern, Koumoutsakos, Petros
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.08.2019 Springer Nature B.V
Témata:	Acceleration Adaptive algorithms Algorithms Bacillus subtilis - genetics Bacillus subtilis - metabolism Biochemical Phenomena Cell Biology Computer Simulation Dimerization Escherichia coli - genetics Escherichia coli - metabolism Escherichia coli Proteins - genetics Escherichia coli Proteins - metabolism Kinetics Lac Operon Life Sciences Markov Chains Mathematical and Computational Biology Mathematical Concepts Mathematics Mathematics and Statistics Models, Biological Monosaccharide Transport Proteins - genetics Monosaccharide Transport Proteins - metabolism Sampling Special Issue: Gillespie and His Algorithms Stochastic Processes Symporters - genetics Symporters - metabolism Systems Biology Stochastic simulation algorithms Stiff systems Accelerated simulation
ISSN:	0092-8240, 1522-9602, 1522-9602
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Popis
Shrnutí:	We propose the S -leaping algorithm for the acceleration of Gillespie’s stochastic simulation algorithm that combines the advantages of the two main accelerated methods; the τ -leaping and R -leaping algorithms. These algorithms are known to be efficient under different conditions; the τ -leaping is efficient for non-stiff systems or systems with partial equilibrium, while the R -leaping performs better in stiff system thanks to an efficient sampling procedure. However, even a small change in a system’s set up can critically affect the nature of the simulated system and thus reduce the efficiency of an accelerated algorithm. The proposed algorithm combines the efficient time step selection from the τ -leaping with the effective sampling procedure from the R -leaping algorithm. The S -leaping is shown to maintain its efficiency under different conditions and in the case of large and stiff systems or systems with fast dynamics, the S -leaping outperforms both methods. We demonstrate the performance and the accuracy of the S -leaping in comparison with the τ -leaping and R -leaping on a number of benchmark systems involving biological reaction networks.
Bibliografie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
ISSN:	0092-8240 1522-9602 1522-9602
DOI:	10.1007/s11538-018-0464-9