Utilize este identificador para referenciar este registo: http://hdl.handle.net/1822/46347

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dc.contributor.authorVieira, Vítorpor
dc.contributor.authorMaia, Paulopor
dc.contributor.authorRocha, Isabelpor
dc.contributor.authorRocha, Miguelpor
dc.date.accessioned2017-08-05T15:09:55Z-
dc.date.available2017-08-05T15:09:55Z-
dc.date.issued2017-03-
dc.identifier.citationVieira, Vítor; Maia, Paulo; Rocha, Isabel; Rocha, Miguel, Development of a framework for metabolic pathway analysis-driven strain optimization methods. Interdisciplinary Sciences-Computational Life Sciences, 9(1), 46-55, 2017por
dc.identifier.issn19132751por
dc.identifier.urihttp://hdl.handle.net/1822/46347-
dc.description.abstractGenome-scale metabolic models (GSMMs) have become important assets for rational design of compound overproduction using microbial cell factories. Most computational strain optimization methods (CSOM) using GSMMs, while useful in metabolic engineering, rely on the definition of questionable cell objectives, leading to some bias. Metabolic pathway analysis approaches do not require an objective function. Though their use brings immediate advantages, it has mostly been restricted to small scale models due to computational demands. Additionally, their complex parameterization and lack of intuitive tools pose an important challenge towards making these widely available to the community. Recently, MCSEnumerator has extended the scale of these methods, namely regarding enumeration of minimal cut sets, now able to handle GSMMs. This work proposes a tool implementing this method as a Java library and a plugin within the OptFlux metabolic engineering platform providing a friendly user interface. A standard enumeration problem and pipeline applicable to GSMMs is proposed, making use by the community simpler. To highlight the potential of these approaches, we devised a case study for overproduction of succinate, providing a phenotype analysis of a selected strategy and comparing robustness with a selected solution from a bi-level CSOM.por
dc.description.sponsorshipThe authors thank the project “DeYeastLibrary—Designer yeast strain library optimized for metabolic engineering applications”, Ref. ERA-IB-2/0003/2013, funded by national funds through “Fundação para a Ciência e Tecnologia / Ministério da Ciência, Tecnologia e Ensino Superior”.por
dc.language.isoengpor
dc.publisherSpringer Naturepor
dc.relationinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/137211/PTpor
dc.rightsopenAccesspor
dc.titleDevelopment of a framework for metabolic pathway analysis-driven strain optimization methodspor
dc.typearticle-
dc.peerreviewedyespor
dc.relation.publisherversionhttps://link.springer.com/journal/12539por
dc.commentsCEB46696por
degois.publication.firstPage46por
degois.publication.lastPage55por
degois.publication.issue1por
degois.publication.locationGermany-
degois.publication.volume9por
dc.date.updated2017-08-03T11:03:44Z-
dc.identifier.essn1867-1462por
dc.identifier.doi10.1007/s12539-017-0218-7por
dc.description.publicationversioninfo:eu-repo/semantics/publishedVersionpor
sdum.journalInterdisciplinary Sciences-Computational Life Sciencespor
Aparece nas coleções:CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series

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