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Global identifiability of nonlinear models of biological systems

机译：生物系统非线性模型的全局可辨识性

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摘要

A prerequisite for well-posedness of parameter estimation of biological and physiological systems is a priori global identifiability, a property which concerns uniqueness of the solution for the unknown model parameters. Assessing a priori global identifiability is particularly difficult for nonlinear dynamic models. Various approaches have been proposed in the literature but no solution exists in the general case. Here, the authors present a new algorithm for testing global identifiability of nonlinear dynamic models, based on differential algebra. The characteristic set associated to the dynamic equations is calculated in an efficient way and computer algebra techniques are used to solve the resulting set of nonlinear algebraic equations. The algorithm is capable of handling many features arising in biological system models, including zero initial conditions and time-varying parameters. Examples of usage of the algorithm for analyzing a priori global identifiability of nonlinear models of biological and physiological systems are presented.
机译：生物和生理系统参数估计的正确性的前提是先验全局可识别性，该属性涉及未知模型参数的解的唯一性。对于非线性动力学模型，评估先验全局可识别性尤其困难。文献中已经提出了各种方法，但是在一般情况下不存在解决方案。在这里，作者提出了一种新的算法，用于基于微分代数测试非线性动力学模型的全局可识别性。以有效的方式计算与动力学方程相关的特征集，并使用计算机代数技术来求解所得的非线性代数方程集。该算法能够处理生物系统模型中出现的许多功能，包括零初始条件和时变参数。给出了使用该算法分析生物和生理系统非线性模型的先验全局可识别性的示例。

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