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An Efficient and Very Accurate Method for Calculating Steady-State Sensitivities in Metabolic Reaction Systems

机译:一种高效且精确的代谢反应系统稳态灵敏度计算方法

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Stability and sensitivity analyses of biological systems require the writing of computer code, which is highly dependent on the particular model and burdensome for large systems. We propose a very accurate strategy to overcome this challenge. Its core concept is the conversion of the model into the format of biochemical systems theory (BST), which greatly facilitates the computation of sensitivities. First, the steady state of interest is determined by integrating the model equations toward the steady state and then using a Newton-Raphson method to fine-tune the result. The second step of conversion into the BST format requires several instances of numerical differentiation. The accuracy of this task is ensured by the use of a complex-variable Taylor scheme for all differentiation steps. The proposed strategy is implemented in a new software program, COSMOS, which automates the stability and sensitivity analysis of essentially arbitrary ODE models in a quick, yet highly accurate manner. The methods underlying the process are theoretically analyzed and illustrated with four representative examples: a simple metabolic reaction model; a model of aspartate-derived amino acid biosynthesis; a TCA-cycle model; and a modified TCA-cycle model. COSMOS has been deposited to https://github.com/ BioprocessdesignLab/COSMOS.
机译:生物系统的稳定性和敏感性分析需要编写计算机代码,这在很大程度上取决于特定的模型,并且对于大型系统而言比较繁琐。我们提出了一种非常准确的策略来克服这一挑战。它的核心概念是将模型转换为生化系统理论(BST)的格式,这极大地促进了灵敏度的计算。首先,通过将模型方程式积分到稳态,然后使用牛顿-拉夫森方法对结果进行微调,来确定目标稳态。转换为BST格式的第二步需要几个数字差异实例。通过对所有微分步骤使用复变量泰勒方案,可以确保此任务的准确性。所提出的策略在新的软件程序COSMOS中实现,该程序以快速但高度准确的方式自动对基本任意ODE模型进行稳定性和灵敏度分析。从理论上分析了该过程的基础方法,并通过四个代表性的例子进行了说明:简单的代谢反应模型;天冬氨酸衍生的氨基酸生物合成模型; TCA周期模型;以及经过修改的TCA周期模型。 COSMOS已保存到https://github.com/ BioprocessdesignLab / COSMOS。

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