Methods for checking structural identifiability of nonlinear biosystems: A critical comparison

Autor:	Eva Balsa-Canto, Julio R. Banga, Oana Chiş
Jazyk:	angličtina
Rok vydání:	2011
Předmět:	Structure (mathematical logic) Controllability Mathematical optimization (structural) identifiability Observability Scale (ratio) computer.software_genre Nonlinear system Generating series Identifiability Data mining Parametric identification computer Mathematics Biological models
Zdroj:	Digital.CSIC. Repositorio Institucional del CSIC instname
Popis:	6 pages, 2 figures, 1 table Model parametric identification is a critical yet often overlooked step for the modelling of biosystems. Modern experimental techniques can be used to obtain time-series data which may then be used to estimate model parameters. However, in many cases, a subset of model parameters may not be uniquely estimated, independently of the quantity and quality of data available or the numerical techniques used for estimation. This lack of identifiability is related to the structure of the model. This work presents a review and a critical comparison of methods to analyze the structural identifiability of non-linear models. Three examples, of increasing level of complexity, related to the modelling of biochemical networks, will be used to illustrate advantages and disadvantages of the available techniques. Results reveal that the generating series approach combined with the identifiability tableau is the most promising to analyze large scale highly nonlinear models
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4fed305aabd3e5a1527f42da0a4fbd94 http://hdl.handle.net/10261/279781 Zobrazit plný text záznamu