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dc.contributor.authorHidalgo, José F. 
dc.contributor.authorEgea Larrosa, José Alberto 
dc.contributor.authorGuil, Francisco 
dc.contributor.authorGarcía, José M. 
dc.date.accessioned2019-05-24T07:18:44Z
dc.date.available2019-05-24T07:18:44Z
dc.date.issued2018-11-20
dc.identifier.citationJosé F. Hidalgo, Jose A. Egea, Francisco Guil and José M. García. Improving the EFMs quality by augmenting their representativeness in LP methods. En 5th International Work-Conference on Bioinformatics and Biomedical Engineering Granada, Spain. 26–28 April 2017es_ES
dc.identifier.issn1752-0509
dc.description.abstractBackground Although cellular metabolism has been widely studied, its fully comprehension is still a challenge. A main tool for this study is the analysis of meaningful pieces of knowledge called modes and, in particular, specially interesting classes of modes such as pathways and Elementary Flux Modes (EFMs). Its study often has to deal with issues such as the appearance of infeasibilities or the difficulty of finding representative enough sets of modes that are free of repetitions. Mode extraction methods usually incorporate strategies devoted to mitigate this phenomena but they still get a high ratio of repetitions in the set of solutions. Results This paper presents a proposal to improve the representativeness of the full set of metabolic reactions in the set of computed modes by penalizing the eventual high frequency of occurrence of some reactions during the extraction. This strategy can be applied to any linear programming based extraction existent method. Conclusions Our strategy enhances the quality of a set of extracted EFMs favouring the presence of every reaction in it and improving the efficiency by mitigating the occurrence of repeated solutions. The new proposed strategy can complement other EFMs extraction methods based on linear programming. The obtained solutions are more likely to be diverse using less computing effort and improving the efficiency of the extraction.es_ES
dc.description.sponsorshipPublication cost of this article was funded by the Spanish Ministerio de Economia y Competitividad (MINECO) and European Commission FEDER under grant TIN2015-66972-C5-3-es_ES
dc.formatapplication/pdfes_ES
dc.language.isoenges_ES
dc.publisherBMCes_ES
dc.relation.urihttps://bmcsystbiol.biomedcentral.com/track/pdf/10.1186/s12918-018-0619-1es_ES
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights© The Author(s). 2018
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.titleImproving the EFMs quality by augmenting their representativeness in LP methodses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.subjectMetabolic networkses_ES
dc.subjectPathways and EFMses_ES
dc.subjectRepresentativeness and qualityes_ES
dc.subjectFlux modeses_ES
dc.subjectLinear programminges_ES
dc.subjectSystems biologyes_ES
dc.subject.otherMatemática Aplicadaes_ES
dc.identifier.urihttp://hdl.handle.net/10317/7776
dc.peerreviewSies_ES
dc.identifier.doi10.1186/s12918-018-0619-1
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_ES
dc.subject.unesco12 Matemáticases_ES
dc.contributor.funderMinisterio de Economía, Industria y Competitividades_ES
dc.contributor.funderComisión Europeaes_ES
dc.contributor.funderFondo Europeo de Desarrollo Regionales_ES


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