Testing structural identifiability by a simple scaling method.

ABSTRACT: Successful mathematical modeling of biological processes relies on the expertise of the modeler to capture the essential mechanisms in the process at hand and on the ability to extract useful information from empirical data. A model is said to be structurally unidentifiable, if different quantitative sets of parameters provide the same observable outcome. This is typical (but not exclusive) of partially observed problems in which only a few variables can be experimentally measured. Most of the available methods to test the structural identifiability of a model are either too complex mathematically for the general practitioner to be applied, or require involved calculations or numerical computation for complex non-linear models. In this work, we present a new analytical method to test struc

SUBMITTER: Castro M 

PROVIDER: S-EPMC7665633 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature