An Implementation of The Method of Moments on Chemical Systems with Constant and Time-dependent Rates

Emmanuel Adara, R. B. Sidje
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Abstract

Among numerical techniques used to facilitate the analysis of biochemical reactions, we can use the method of moments to directly approximate statistics such as the mean numbers of molecules. The method is computationally viable in time and memory, compared to solving the chemical master equation (CME) which is notoriously expensive. In this study, we apply the method of moments to a chemical system with a constant rate representing a vascular endothelial growth factor (VEGF) model, as well as another system with time-dependent propensities representing the susceptible, infected, and recovered (SIR) model with periodic contact rate. We assess the accuracy of the method using comparisons with approximations obtained by the stochastic simulation algorithm (SSA) and the chemical Langevin equation (CLE). The VEGF model is of interest because of the role of VEGF in the growth of cancer and other inflammatory diseases and the potential use of anti-VEGF therapies in the treatment of cancer. The SIR model is a popular epidemiological model used in studying the spread of various infectious diseases in a population.
矩量法在常速率和随时间变化的化学系统上的实现
在用于生化反应分析的数值技术中,我们可以使用矩量法直接近似统计数据,如分子的平均数量。与求解化学主方程(CME)相比,该方法在计算时间和内存上是可行的,这是出了名的昂贵。在这项研究中,我们将矩量方法应用于一个具有恒定速率的化学系统,代表血管内皮生长因子(VEGF)模型,以及另一个具有时间依赖倾向的系统,代表具有周期性接触率的易感、感染和恢复(SIR)模型。我们通过与随机模拟算法(SSA)和化学朗之万方程(CLE)获得的近似结果进行比较来评估该方法的准确性。由于VEGF在癌症和其他炎症性疾病的生长中的作用以及抗VEGF疗法在癌症治疗中的潜在应用,VEGF模型引起了人们的兴趣。SIR模型是一种流行的流行病学模型,用于研究各种传染病在人群中的传播。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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