Simultaneous Parameters Identifiability and Estimation of an E. coli Metabolic Network Model.
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 re...
| Publicado en: | BioMed Research International Vol. 2015; pp. 1 - 22 |
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| Autores principales: | , , , , , |
| Formato: | equations & formulas glossary protocol research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
1/6/2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=109273036&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 109273036 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 1/6/2015 vid: 2015 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 109273036 109273036 109273036 10.1155/2015/454765 109273036 ppf: 1 ppct: 21 formats: fmt: @attributes: type: P tig: atl: Simultaneous Parameters Identifiability and Estimation of an E. coli Metabolic Network Model. aug: au: Pontes Freitas Alberton, Kese Alberton, André Luís Di Maggio, Jimena Andrea Estrada, Vanina Gisela Díaz, María Soledad Secchi, Argimiro Resende affil: Programa de Engenharia Química-COPPE, Universidade Federal do Rio de Janeiro, Cidade Universitária, 21941-972 Rio de Janeiro, BR, Brazil sug: subj: Escherichia Coli Physiology Models, Biological Metabolic Networks and Pathways Evaluation Carbon Metabolism Enzymes Metabolism Case Studies Microbiology Descriptive Statistics Data Analysis Software Kinetics Nomenclature Biochemistry Methods Funding Source ab: 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. pubtype: Academic Journal doctype: equations & formulas glossary protocol research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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