Johnston Matthew D, Burton Evan
Department of Mathematics, San José State University, One Washington Square, San Jose, CA, 95192, USA.
Bull Math Biol. 2019 May;81(5):1613-1644. doi: 10.1007/s11538-019-00579-z. Epub 2019 Feb 21.
We present a computational method for performing structural translation, which has been studied recently in the context of analyzing the steady states and dynamical behavior of mass-action systems derived from biochemical reaction networks. Our procedure involves solving a binary linear programming problem where the decision variables correspond to interactions between the reactions of the original network. We call the resulting network a reaction-to-reaction graph and formalize how such a construction relates to the original reaction network and the structural translation. We demonstrate the efficacy and efficiency of the algorithm by running it on 508 networks from the European Bioinformatics Institutes' BioModels database. We also summarize how this work can be incorporated into recently proposed algorithms for establishing mono- and multistationarity in biochemical reaction systems.
我们提出了一种用于执行结构翻译的计算方法，该方法最近在分析源自生化反应网络的质量作用系统的稳态和动力学行为的背景下得到了研究。我们的过程涉及求解一个二元线性规划问题，其中决策变量对应于原始网络反应之间的相互作用。我们将得到的网络称为反应-反应图，并形式化这种构建与原始反应网络和结构翻译的关系。我们通过在欧洲生物信息学研究所的BioModels数据库中的508个网络上运行该算法来证明其有效性和效率。我们还总结了这项工作如何纳入最近提出的用于确定生化反应系统中单稳态和多稳态的算法中。
