A new class of highly efficient exact stochastic simulation algorithms for chemical reaction networks.
We introduce an alternative formulation of the exact stochastic simulation algorithm (SSA) for sampling trajectories of the chemical master equation for a well-stirred system of coupled chemical reactions. Our formulation is based on factored-out, partial reaction propensities. This novel exact SSA, called the partial-propensity direct method (PDM), is highly efficient and has a computational cost that scales at most linearly with the number of chemical species, irrespective of the degree of coupling of the reaction network. In addition, we propose a sorting variant, SPDM, which is especially efficient for multiscale reaction networks.
Ramaswamy
Rajesh
R
Institute of Theoretical Computer Science, ETH Zurich, CH-8092 Zurich, Switzerland. rajeshr@ethz.ch
González-Segredo
Nélido
N
Sbalzarini
Ivo F
IF
D000465:Algorithms; D003102:Colloids / Q000737:chemistry; D003198:Computer Simulation; D004926:Escherichia coli / Q000235:genetics / Q000378:metabolism; D029968:Escherichia coli Proteins / Q000235:genetics / Q000378:metabolism; D006360:Heat-Shock Proteins / Q000235:genetics / Q000378:metabolism; D008954:Models, Biological; D008956:Models, Chemical; D013269:Stochastic Processes
D003102:Colloids; D029968:Escherichia coli Proteins; D006360:Heat-Shock Proteins