Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA.
J Chem Phys. 2013 Sep 21;139(11):115105. doi: 10.1063/1.4821167.
We apply the "weighted ensemble" (WE) simulation strategy, previously employed in the context of molecular dynamics simulations, to a series of systems-biology models that range in complexity from a one-dimensional system to a system with 354 species and 3680 reactions. WE is relatively easy to implement, does not require extensive hand-tuning of parameters, does not depend on the details of the simulation algorithm, and can facilitate the simulation of extremely rare events. For the coupled stochastic reaction systems we study, WE is able to produce accurate and efficient approximations of the joint probability distribution for all chemical species for all time t. WE is also able to efficiently extract mean first passage times for the systems, via the construction of a steady-state condition with feedback. In all cases studied here, WE results agree with independent "brute-force" calculations, but significantly enhance the precision with which rare or slow processes can be characterized. Speedups over "brute-force" in sampling rare events via the Gillespie direct Stochastic Simulation Algorithm range from ~10(12) to ~10(18) for characterizing rare states in a distribution, and ~10(2) to ~10(4) for finding mean first passage times.
我们将“加权集成”（WE）模拟策略应用于一系列系统生物学模型，这些模型的复杂程度从一维系统到具有 354 个物种和 3680 个反应的系统不等。WE 相对容易实现，不需要广泛地调整参数，不依赖于模拟算法的细节，并且可以促进对极罕见事件的模拟。对于我们研究的耦合随机反应系统，WE 能够在所有时间 t 为所有化学物质产生联合概率分布的准确而有效的近似值。WE 还能够通过构建具有反馈的稳态条件，有效地提取系统的平均首次通过时间。在所有在这里研究的情况下，WE 的结果与独立的“暴力”计算一致，但显著提高了对稀有或缓慢过程进行特征描述的精度。通过 Gillespie 直接随机模拟算法对稀有事件进行采样的“暴力”计算的加速范围从对分布中的稀有状态进行特征描述的10(12)到10(18)，以及寻找平均首次通过时间的10(2)到10(4)。
