The input-output relationship approach to structural identifiability analysis
The input-output relationship approach to structural identifiability analysis
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DOI：
10.1016/j.cmpb.2012.10.012
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发表时间：
2013-02-01
影响因子：
6.1
通讯作者：
Chappell, Michael J.
中科院分区：
文献类型：
--
作者：
Bearup, Daniel J.;Evans, Neil D.;Chappell, Michael J.
分析给定模型系统的可辨识性是从物理数据确定模型参数的必要前提。然而，可用于分析非线性系统的工具可能在适用性和计算困难性方面受到限制，但对于最简单的模型。模型的输入-输出关系概括了整个系统的输入-输出结构，因此为这种分析提供了另一种方法的可能性，然而，为了使这种方法有效，有必要确定微分多项式的单项式是否线性独立。在这项工作中提出了一个简单的测试此属性。这种关系的推导和分析可以在Maple中符号化地实现。这些技术被应用于分析经典的生物医学系统建模和酶催化反应方案的模型。(C)2012爱思唯尔爱尔兰有限公司保留所有权利。
Analysis of the identifiability of a given model system is an essential prerequisite to the determination of model parameters from physical data. However, the tools available for the analysis of non-linear systems can be limited both in applicability and by computational intractability for any but the simplest of models. The input-output relation of a model summarises the input-output structure of the whole system and as such provides the potential for an alternative approach to this analysis, However for this approach to be valid it is necessary to determine whether the monomials of a differential polynomial are linearly independent. A simple test for this property is presented in this work. The derivation and analysis of this relation can be implemented symbolically within Maple. These techniques are applied to analyse classical models from biomedical systems modelling and those of enzyme catalysed reaction schemes. (C) 2012 Elsevier Ireland Ltd. All rights reserved.