Structural Identifiability of Dynamic Systems Biology Models.

ABSTRACT: A powerful way of gaining insight into biological systems is by creating a nonlinear differential equation model, which usually contains many unknown parameters. Such a model is called structurally identifiable if it is possible to determine the values of its parameters from measurements of the model outputs. Structural identifiability is a prerequisite for parameter estimation, and should be assessed before exploiting a model. However, this analysis is seldom performed due to the high computational cost involved in the necessary symbolic calculations, which quickly becomes prohibitive as the problem size increases. In this paper we show how to analyse the structural identifiability of a very general class of nonlinear models by extending methods originally developed for studying observabi

SUBMITTER: Villaverde AF 

PROVIDER: S-EPMC5085250 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature