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Path finding methods accounting for stoichiometry in metabolic networks

Graph-based methods have been widely used for the analysis of biological networks. Their application to metabolic networks has been much discussed, in particular noting that an important weakness in such methods is that reaction stoichiometry is neglected. In this study, we show that reaction stoich...

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Detalles Bibliográficos
Autores principales: Pey, Jon, Prada, Joaquín, Beasley, John E, Planes, Francisco J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3219972/
https://www.ncbi.nlm.nih.gov/pubmed/21619601
http://dx.doi.org/10.1186/gb-2011-12-5-r49
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author Pey, Jon
Prada, Joaquín
Beasley, John E
Planes, Francisco J
author_facet Pey, Jon
Prada, Joaquín
Beasley, John E
Planes, Francisco J
author_sort Pey, Jon
collection PubMed
description Graph-based methods have been widely used for the analysis of biological networks. Their application to metabolic networks has been much discussed, in particular noting that an important weakness in such methods is that reaction stoichiometry is neglected. In this study, we show that reaction stoichiometry can be incorporated into path-finding approaches via mixed-integer linear programming. This major advance at the modeling level results in improved prediction of topological and functional properties in metabolic networks.
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spelling pubmed-32199722011-11-18 Path finding methods accounting for stoichiometry in metabolic networks Pey, Jon Prada, Joaquín Beasley, John E Planes, Francisco J Genome Biol Method Graph-based methods have been widely used for the analysis of biological networks. Their application to metabolic networks has been much discussed, in particular noting that an important weakness in such methods is that reaction stoichiometry is neglected. In this study, we show that reaction stoichiometry can be incorporated into path-finding approaches via mixed-integer linear programming. This major advance at the modeling level results in improved prediction of topological and functional properties in metabolic networks. BioMed Central 2011 2011-05-27 /pmc/articles/PMC3219972/ /pubmed/21619601 http://dx.doi.org/10.1186/gb-2011-12-5-r49 Text en Copyright ©2011 Pey et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Method
Pey, Jon
Prada, Joaquín
Beasley, John E
Planes, Francisco J
Path finding methods accounting for stoichiometry in metabolic networks
title Path finding methods accounting for stoichiometry in metabolic networks
title_full Path finding methods accounting for stoichiometry in metabolic networks
title_fullStr Path finding methods accounting for stoichiometry in metabolic networks
title_full_unstemmed Path finding methods accounting for stoichiometry in metabolic networks
title_short Path finding methods accounting for stoichiometry in metabolic networks
title_sort path finding methods accounting for stoichiometry in metabolic networks
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3219972/
https://www.ncbi.nlm.nih.gov/pubmed/21619601
http://dx.doi.org/10.1186/gb-2011-12-5-r49
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