S-Leaping: An Adaptive, Accelerated Stochastic Simulation Algorithm, Bridging [Formula: see text]-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 [Formula: see text]-leaping and R-leaping algorithms. These algorithms are known to be efficient under different conditions; the [Formula: see text]-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 [Formula: see text]-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 [Formula: see text]-leaping and R-leaping on a number of benchmark systems involving biological reaction networks.
['Lipková|Jana|J|', 'Arampatzis|Georgios|G|', 'Chatelain|Philippe|P|', 'Menze|Bjoern|B|', 'Koumoutsakos|Petros|P|0000-0001-8337-2122']
D000465:Algorithms D001412:Bacillus subtilis D001669:Biochemical Phenomena D003198:Computer Simulation D019281:Dimerization D004926:Escherichia coli D029968:Escherichia coli Proteins D007700:Kinetics D007763:Lac Operon D008390:Markov Chains D055641:Mathematical Concepts D008954:Models, Biological D009004:Monosaccharide Transport Proteins D013269:Stochastic Processes D027981:Symporters D049490:Systems Biology
Stochastic simulation algorithms Stiff systems Accelerated simulation