Liu Z, Cao Y
Virginia Tech, Department of Computer Science, Blacksburg, VA 24061, USA.
IET Syst Biol. 2008 Sep;2(5):334-41. doi: 10.1049/iet-syb:20070074.
Morton-Firth and Bray's stochastic simulator (StochSim) and Gillespie's stochastic simulation algorithm (SSA) are two important methods for stochastic modelling and simulation of biochemical systems. They have been widely applied to different biological problems. A key question is discussed here: Are these two methods equivalent? These two methods are compared using fundamental probability analysis. The analysis clearly shows that, when the time step in the StochSim is chosen very small, the StochSim can be viewed as a first-order approximation to the SSA. The analysis also explains why the SSA is usually much more efficient than the StochSim for biochemical systems. However, when multistate species present in a system, the StochSim clearly shows its advantage. The Complexity analysis is used to explain this advantage. The hybrid SSA (HSSA) is proposed to combine the advantages of both the StochSim and SSA. When the populations of the multistate species are small, the HSSA is very efficient. Numerical experiments are presented to verify the analysis.
莫顿 - 弗思和布雷的随机模拟器（StochSim）以及吉莱斯皮的随机模拟算法（SSA）是生化系统随机建模与模拟的两种重要方法。它们已被广泛应用于不同的生物学问题。这里讨论一个关键问题：这两种方法等效吗？使用基本概率分析对这两种方法进行比较。分析清楚地表明，当StochSim中的时间步长选择得非常小时，StochSim可被视为对SSA的一阶近似。该分析还解释了为什么对于生化系统，SSA通常比StochSim效率高得多。然而，当系统中存在多状态物种时，StochSim明显显示出其优势。使用复杂度分析来解释这一优势。提出了混合SSA（HSSA）以结合StochSim和SSA的优点。当多状态物种的数量较少时，HSSA非常高效。给出了数值实验以验证该分析。
