Evidence map›Paper›PMID 25654103›Full record

ArticleBioMed research international2015

Simultaneous parameters identifiability and estimation of an E. coli metabolic network model.

Kese Pontes Freitas Alberton, André Luís Alberton, Jimena Andrea Di Maggio, Vanina Gisela Estrada, María Soledad Díaz, Argimiro Resende Secchi

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Article in BioMed research international, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Frontiers in chemistry · 2020
    Article
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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Kese Pontes Freitas AlbertonPrograma de Engenharia Química-COPPE, Universidade Federal do Rio de Janeiro, Cidade Universitária, 21941-972 Rio de Janeiro, BR, Brazil.ORCID 0000-0002-6210-5698
André Luís AlbertonInstituto de Química, Universidade do Estado do Rio de Janeiro, São Francisco Xavier 524, 20550-900 Rio de Janeiro, BR, Brazil.
Jimena Andrea Di MaggioPlanta Piloto de Ingeniería Química-CONICET, Universidad Nacional del Sur, Camino La Carrindanga, Km 7, 8000 Bahía Blanca, Argentina.
Vanina Gisela EstradaPlanta Piloto de Ingeniería Química-CONICET, Universidad Nacional del Sur, Camino La Carrindanga, Km 7, 8000 Bahía Blanca, Argentina.
María Soledad DíazPlanta Piloto de Ingeniería Química-CONICET, Universidad Nacional del Sur, Camino La Carrindanga, Km 7, 8000 Bahía Blanca, Argentina.
Argimiro Resende SecchiPrograma de Engenharia Química-COPPE, Universidade Federal do Rio de Janeiro, Cidade Universitária, 21941-972 Rio de Janeiro, BR, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Metabolic Networks and PathwaysModels, BiologicalCarbonEscherichia coli K12Numerical Analysis, Computer-AssistedCarbon

Identifiers

PMID25654103
PMCPMC4303013

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.