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Flux Coupling and the Objective Functions’ Length in EFMs

Structural analysis of constraint-based metabolic network models attempts to find the network’s properties by searching for subsets of suitable modes or Elementary Flux Modes (EFMs). One useful approach is based on Linear Program (LP) techniques, which introduce an objective function to convert the...

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Detalles Bibliográficos
Autores principales: Guil, Francisco, Hidalgo, José F., García, José M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7759806/
https://www.ncbi.nlm.nih.gov/pubmed/33260526
http://dx.doi.org/10.3390/metabo10120489
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author Guil, Francisco
Hidalgo, José F.
García, José M.
author_facet Guil, Francisco
Hidalgo, José F.
García, José M.
author_sort Guil, Francisco
collection PubMed
description Structural analysis of constraint-based metabolic network models attempts to find the network’s properties by searching for subsets of suitable modes or Elementary Flux Modes (EFMs). One useful approach is based on Linear Program (LP) techniques, which introduce an objective function to convert the stoichiometric and thermodynamic constraints into a linear program (LP), using additional constraints to generate different nontrivial modes. This work introduces FLFS-FC (Fixed Length Function Sampling with Flux Coupling), a new approach to increase the efficiency of generation of large sets of different EFMs for the network. FLFS-FC is based on the importance of the length of the objective functions used in the associated LP problem and the imposition of additional negative constraints. Our proposal overrides some of the known drawbacks associated with the EFM extraction, such as the appearance of unfeasible problems or multiple repeated solutions arising from different LP problems.
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spelling pubmed-77598062020-12-26 Flux Coupling and the Objective Functions’ Length in EFMs Guil, Francisco Hidalgo, José F. García, José M. Metabolites Article Structural analysis of constraint-based metabolic network models attempts to find the network’s properties by searching for subsets of suitable modes or Elementary Flux Modes (EFMs). One useful approach is based on Linear Program (LP) techniques, which introduce an objective function to convert the stoichiometric and thermodynamic constraints into a linear program (LP), using additional constraints to generate different nontrivial modes. This work introduces FLFS-FC (Fixed Length Function Sampling with Flux Coupling), a new approach to increase the efficiency of generation of large sets of different EFMs for the network. FLFS-FC is based on the importance of the length of the objective functions used in the associated LP problem and the imposition of additional negative constraints. Our proposal overrides some of the known drawbacks associated with the EFM extraction, such as the appearance of unfeasible problems or multiple repeated solutions arising from different LP problems. MDPI 2020-11-28 /pmc/articles/PMC7759806/ /pubmed/33260526 http://dx.doi.org/10.3390/metabo10120489 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Guil, Francisco
Hidalgo, José F.
García, José M.
Flux Coupling and the Objective Functions’ Length in EFMs
title Flux Coupling and the Objective Functions’ Length in EFMs
title_full Flux Coupling and the Objective Functions’ Length in EFMs
title_fullStr Flux Coupling and the Objective Functions’ Length in EFMs
title_full_unstemmed Flux Coupling and the Objective Functions’ Length in EFMs
title_short Flux Coupling and the Objective Functions’ Length in EFMs
title_sort flux coupling and the objective functions’ length in efms
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7759806/
https://www.ncbi.nlm.nih.gov/pubmed/33260526
http://dx.doi.org/10.3390/metabo10120489
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