title: A new class of highly efficient exact stochastic simulation algorithms for chemical reaction networks.
abstract: 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.
authors: Institute of Theoretical Computer Science, ETH Zurich, CH-8092 Zurich, Switzerland. rajeshr@ethz.ch
authors: Rajesh
authors: R
authors: Ramaswamy
authors: Nélido
authors: N
authors: González-Segredo
authors: Ivo F
authors: IF
authors: Sbalzarini
mesh_terms: 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
chemical_list: D003102:Colloids; D029968:Escherichia coli Proteins; D006360:Heat-Shock Proteins