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Robust Sampling Time Design for Biochemical Systems

机译:生化系统的稳健采样时间设计

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Optimal sampling time design by considering parameter uncertainties has rarely been considered in published research. In this work, the robust experimental design (RED) for sampling time selection is investigated. The aim is to exploit the sampling strategy using which the experiment can provide the most informative data for improving parameter estimation quality. With an enzyme reaction case study system, two global sensitivity analysis (GSA) approaches, the Morris screening method and the Sobol’s method, are firstly applied to find out the key parameters that have large influences to model outputs of interest. Then three different RED methods, the worst-case strategy, the Bayesian design, and the GSA-based approach, are developed to design the optimal sampling time schedule. Simulation results suggest that, among the three RED methods, the equally spaced sampling from the Bayesian design has the best robustness towards parameter uncertainties.
机译:通过考虑参数不确定性的最佳采样时间设计在公开的研究中很少被考虑。在这项工作中,研究了用于采样时间选择的鲁棒实验设计(RED)。目的是利用采样策略,通过该策略,实验可以提供最有用的数据,从而提高参数估计质量。借助酶反应案例研究系统,首先应用了两种全局敏感性分析(GSA)方法,即莫里斯筛选方法和Sobol方法,以找出对模型输出影响较大的关键参数。然后,开发了三种不同的RED方法,最坏情况策略,贝叶斯设计和基于GSA的方法,以设计最佳采样时间表。仿真结果表明,在三种RED方法中,贝叶斯设计的等距采样对参数不确定性具有最佳的鲁棒性。

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