Institute of Theoretical Computer Science and Swiss Institute of Bioinformatics, ETH Zurich, CH-8092 Zürich, Switzerland.
J Chem Phys. 2010 Jan 28;132(4):044102. doi: 10.1063/1.3297948.
We present the partial-propensity stochastic simulation algorithm with composition-rejection sampling (PSSA-CR). It is an exact formulation of the stochastic simulation algorithm (SSA) for well-stirred systems of coupled chemical reactions. The new formulation is a partial-propensity variant [R. Ramaswamy, N. Gonzalez-Segredo, and I. F. Sbalzarini, J. Chem. Phys. 130, 244104 (2009)] of the composition- rejection SSA [A. Slepoy, A. P. Thompson, and S. J. Plimpton, J. Chem. Phys. 128, 205101 (2008)]. The computational cost of this new formulation is bounded by a constant for weakly coupled reaction networks, and it increases at most linearly with the number of chemical species for strongly coupled reaction networks. PSSA-CR thus combines the advantages of partial-propensity methods and the composition-rejection SSA, providing favorable scaling of the computational cost for all classes of reaction networks.
我们提出了带有组成拒绝采样的部分倾向性随机模拟算法 (PSSA-CR)。它是耦合化学反应的完全搅拌系统的随机模拟算法 (SSA) 的精确公式。新公式是组成拒绝 SSA 的部分倾向性变体[R. Ramaswamy、N. Gonzalez-Segredo 和 I. F. Sbalzarini,J. Chem. Phys. 130, 244104 (2009)]。对于弱耦合反应网络,该新公式的计算成本受常数限制,对于强耦合反应网络,其计算成本最多线性增加。因此,PSSA-CR 结合了部分倾向性方法和组成拒绝 SSA 的优点,为所有类型的反应网络提供了有利的计算成本扩展。