INVESTIGADORES
DIAZ Maria Soledad
artículos
Título:
Simultaneous Parameters Identifiability and Estimation of an E. coli Metabolic Network Model
Autor/es:
KESE P. F. ALBERTON; ANDRE LUIS ALBERTON; JIMENA DI MAGGIO; VANINA G. ESTRADA; MARIA SOLEDAD DIAZ; ARGIMIRO R. SECCHI
Revista:
BIOMED RES INT (ex J BIOMED BIOTECHNOL
Editorial:
Hindawi Publishing Corporation
Referencias:
Lugar: New York; Año: 2015 vol. 2015 p. 1 - 21
ISSN:
2314-6133
Resumen:
This work proposes a procedure for simultaneous parameters identifiability and estimation in metabolic networks in order to
overcome difficulties associated with lack of experimental data and large number of parameters, a common scenario in themodeling
of such systems. As case study, the complex real problem of parameters identifiability of the Escherichia coli K-12 W3110 dynamic
model was investigated, composed by 18 differential ordinary equations and 35 kinetic rates, containing 125 parameters. With the
procedure, model fit was improved formost of the measured metabolites, achieving 58 parameters estimated, including 5 unknown
initial conditions.The results indicate that simultaneous parameters identifiability and estimation approach in metabolic networks
is appealing, since model fit to the most of measured metabolites was possible even when important measures of intracellular
metabolites and good initial estimates of parameters are not available