Centrum Wiskunde and Informatica, Amsterdam, The Netherlands.
Math Biosci. 2010 Feb;223(2):83-96. doi: 10.1016/j.mbs.2009.11.002. Epub 2009 Nov 12.
Since analysis and simulation of biological phenomena require the availability of their fully specified models, one needs to be able to estimate unknown parameter values of the models. In this paper we deal with identifiability of parametrizations which is the property of one-to-one correspondence of parameter values and the corresponding outputs of the models. Verification of identifiability of a parametrization precedes estimation of numerical values of parameters, and thus determination of a fully specified model of a considered phenomenon. We derive necessary and sufficient conditions for the parametrizations of polynomial and rational systems to be structurally or globally identifiable. The results are applied to investigate the identifiability properties of the system modeling a chain of two enzyme-catalyzed irreversible reactions. The other examples deal with the phenomena modeled by using Michaelis-Menten kinetics and the model of a peptide chain elongation.
由于分析和模拟生物现象需要有其完整指定模型的支持，因此需要能够估计模型中未知参数的值。在本文中，我们处理参数化的可识别性问题，这是参数值和模型对应输出之间一一对应关系的属性。参数化的可识别性验证先于参数数值的估计，因此确定所考虑现象的完整指定模型。我们推导出多项式和有理系统参数化在结构上或全局上可识别的充要条件。这些结果应用于研究模拟两个酶促不可逆反应链的系统的可识别性特性。其他示例涉及使用米氏动力学和肽链延伸模型建模的现象。
