A new class of highly efficient exact stochastic simulation algorithms for chemical reaction networks

J Chem Phys. 2009 Jun 28;130(24):244104. doi: 10.1063/1.3154624.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Colloids / chemistry
  • Computer Simulation
  • Escherichia coli / genetics
  • Escherichia coli / metabolism
  • Escherichia coli Proteins / genetics
  • Escherichia coli Proteins / metabolism
  • Heat-Shock Proteins / genetics
  • Heat-Shock Proteins / metabolism
  • Models, Biological
  • Models, Chemical*
  • Stochastic Processes*

Substances

  • Colloids
  • Escherichia coli Proteins
  • Heat-Shock Proteins