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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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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. |
format | Online Article Text |
id | pubmed-3219972 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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