Hybrid moment computation algorithm for biochemical reaction networks
Hybrid moment computation algorithm for biochemical reaction networks
复制标题
生化反应网络的混合矩计算算法
DOI：
10.1109/cdc.2010.5717819
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
J. Hespanha
中科院分区：
文献类型：
--
作者：
Yun‐Bo Zhao;Jongrae Kim;J. Hespanha
矩计算对于生化反应网络的随机动力学模型的分析至关重要。通常的情况是，矩演化，通常是随时间的第一和第二矩演化，都是感兴趣的信息。然而，力矩计算的潜在方法，特别是力矩闭合方法和精确随机模拟方法，有其显着的缺陷。前者尽管计算效率高，但本质上是真实解的近似，因此在某些条件下缺乏准确性，而计算效率低下使得后者的使用仅限于分子数量较少的网络。因此，结合力矩闭合方法和精确随机模拟算法，提出了一种混合力矩计算算法。矩量收敛法和随机模拟算法轮流运行，以达到矩量收敛法的效率和随机模拟的精度之间的最佳平衡。该混合算法应用于盘基网柄菌 cAMP 振荡网络。仿真结果说明了算法的有效性。
Moment computation is essential to the analysis of stochastic kinetic models of biochemical reaction networks. It is often the case that the moment evolution, usually the first and the second moment evolutions over time, is all the information of interest. However, potential approaches to moment computation, specifically, the moment closure method and the exact stochastic simulation method, have their significant deficiency. The former, despite its computational efficiency, is essentially an approximation to the real solution and thus is lack of inaccuracy at certain conditions, while the computational inefficiency makes the usage of the latter limited to the networks with small number of molecules. A hybrid moment computation algorithm is therefore proposed by integrating the moment closure method and the exact stochastic simulation algorithms. The moment closure method and the stochastic simulation algorithm operate by turns to achieve an optimal balance between the efficiency due to the moment closure method and the accuracy due to the stochastic simulation. The hybrid algorithm is applied to a Dictyostelium cAMP oscillation network. The simulation results illustrate the effectiveness of the algorithm.
影响因子：
3.3
作者：
Laub, MT;Loomis, WF
通讯作者：
Loomis, WF
使用广义奈奎斯特稳定性准则评估生物分子网络的随机效应
影响因子：
6.8
作者：
Jongrae Kim
通讯作者：
Jongrae Kim