Thanh Vo Hong, Priami Corrado
The Microsoft Research - University of Trento Centre for Computational and Systems Biology, Piazza Manifattura 1, Rovereto 38068, Italy.
J Chem Phys. 2015 Aug 7;143(5):054104. doi: 10.1063/1.4927916.
We address the problem of simulating biochemical reaction networks with time-dependent rates and propose a new algorithm based on our rejection-based stochastic simulation algorithm (RSSA) [Thanh et al., J. Chem. Phys. 141(13), 134116 (2014)]. The computation for selecting next reaction firings by our time-dependent RSSA (tRSSA) is computationally efficient. Furthermore, the generated trajectory is exact by exploiting the rejection-based mechanism. We benchmark tRSSA on different biological systems with varying forms of reaction rates to demonstrate its applicability and efficiency. We reveal that for nontrivial cases, the selection of reaction firings in existing algorithms introduces approximations because the integration of reaction rates is very computationally demanding and simplifying assumptions are introduced. The selection of the next reaction firing by our approach is easier while preserving the exactness.
我们解决了模拟具有时间依赖性反应速率的生化反应网络的问题,并基于我们的基于拒绝的随机模拟算法(RSSA)[Thanh等人,《化学物理杂志》141(13),134116(2014)]提出了一种新算法。通过我们的时间依赖性RSSA(tRSSA)选择下一次反应触发的计算效率很高。此外,通过利用基于拒绝的机制,生成的轨迹是精确的。我们在具有不同反应速率形式的不同生物系统上对tRSSA进行基准测试以证明其适用性和效率。我们发现,对于非平凡情况,现有算法中反应触发的选择会引入近似值,因为反应速率的积分在计算上要求很高且引入了简化假设。我们的方法在保持精确性的同时更容易选择下一次反应触发。