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BioMed Research International
Volume 2015 (2015), Article ID 454765, 21 pages
http://dx.doi.org/10.1155/2015/454765
Research Article

Simultaneous Parameters Identifiability and Estimation of an E. coli Metabolic Network Model

1Programa de Engenharia Química-COPPE, Universidade Federal do Rio de Janeiro, Cidade Universitária, 21941-972 Rio de Janeiro, BR, Brazil
2Instituto de Química, Universidade do Estado do Rio de Janeiro, São Francisco Xavier 524, 20550-900 Rio de Janeiro, BR, Brazil
3Planta Piloto de Ingeniería Química-CONICET, Universidad Nacional del Sur, Camino La Carrindanga, Km 7, 8000 Bahía Blanca, Argentina

Received 31 May 2014; Revised 29 August 2014; Accepted 5 September 2014

Academic Editor: Eugénio Ferreira

Copyright © 2015 Kese Pontes Freitas Alberton et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

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 the modeling 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 for most 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.