Parameter identifiability of cardiac ionic models using a novel CellML least squares optimization tool.
Annu Int Conf IEEE Eng Med Biol Soc
; 2007: 5307-10, 2007.
Article
em En
| MEDLINE
| ID: mdl-18003205
ABSTRACT
Published models of excitable cells can be used to fit to a range of action potential experimental data. CellML is a well-defined standard for publishing and exchanging such models, but currently there is a lack of software that utilizes CellML for parameter analysis. In this paper, we introduce a Java-based utility capable of performing model simulation, identifiability analysis, and parameter optimization of ionic cardiac cell models written in CellML. Identifiability analysis was performed in seven CellML models. Parameter identifiability was consistently improved by using the compensatory membrane current as opposed to the membrane voltage as the residual. as well as through the introduction of an additional stimulus set used in the fitting process.
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Base de dados:
MEDLINE
Assunto principal:
Linguagens de Programação
/
Interface Usuário-Computador
/
Miócitos Cardíacos
/
Sistema de Condução Cardíaco
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Canais Iônicos
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Modelos Cardiovasculares
Idioma:
En
Ano de publicação:
2007
Tipo de documento:
Article