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http://hdl.handle.net/10261/192442
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Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE | |
Campo DC | Valor | Lengua/Idioma |
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dc.contributor.author | García-Jiménez, Beatriz | es_ES |
dc.contributor.author | García, José Luis | es_ES |
dc.contributor.author | Nogales, Juan | es_ES |
dc.date.accessioned | 2019-10-10T12:35:49Z | - |
dc.date.available | 2019-10-10T12:35:49Z | - |
dc.date.issued | 2018-09-01 | - |
dc.identifier.citation | Bioinformatics 34 (17) i954–i963 (2018) | es_ES |
dc.identifier.issn | 1367-4803 | - |
dc.identifier.uri | http://hdl.handle.net/10261/192442 | - |
dc.description | 10 p.-5 fig.-2 tab. | es_ES |
dc.description.abstract | Motivation Synthetic microbial communities begin to be considered as promising multicellular biocatalysts having a large potential to replace engineered single strains in biotechnology applications, in pharmaceutical, chemical and living architecture sectors. In contrast to single strain engineering, the effective and high-throughput analysis and engineering of microbial consortia face the lack of knowledge, tools and well-defined workflows. This manuscript contributes to fill this important gap with a framework, called FLYCOP (FLexible sYnthetic Consortium OPtimization), which contributes to microbial consortia modeling and engineering, while improving the knowledge about how these communities work. FLYCOP selects the best consortium configuration to optimize a given goal, among multiple and diverse configurations, in a flexible way, taking temporal changes in metabolite concentrations into account. | es_ES |
dc.description.abstract | Results In contrast to previous systems optimizing microbial consortia, FLYCOP has novel characteristics to face up to new problems, to represent additional features and to analyze events influencing the consortia behavior. In this manuscript, FLYCOP optimizes a Synechococcus elongatus-Pseudomonas putida consortium to produce the maximum amount of bio-plastic (PHA, polyhydroxyalkanoate), and highlights the influence of metabolites exchange dynamics in a four auxotrophic Escherichia coli consortium with parallel growth. FLYCOP can also provide an explanation about biological evolution driving evolutionary engineering endeavors by describing why and how heterogeneous populations emerge from monoclonal ones. | es_ES |
dc.description.abstract | Availability and implementation Code reproducing the study cases described in this manuscript are available on-line: https://github.com/beatrizgj/FLYCOP | es_ES |
dc.description.abstract | Supplementary information Supplementary data are available at Bioinformatics online. | es_ES |
dc.description.abstract | Issue Section: SYSTEMS | es_ES |
dc.description.sponsorship | This work was supported from the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement no 686585, and the Spanish Ministry of Economy and Competitivity through the RobDcode grant (BIO2014-59528-JIN). | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Oxford University Press | es_ES |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/686585 | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/BIO2014-59528-JIN | es_ES |
dc.relation.isversionof | Publisher's version | es_ES |
dc.rights | openAccess | es_ES |
dc.title | FLYCOP: metabolic modeling-based analysis and engineering microbial communities | es_ES |
dc.type | artículo | es_ES |
dc.identifier.doi | 10.1093/bioinformatics/bty561 | - |
dc.description.peerreviewed | Peer reviewed | es_ES |
dc.relation.publisherversion | https://doi.org/10.1093/bioinformatics/bty561 | es_ES |
dc.identifier.e-issn | 1460-2059 | - |
dc.rights.license | https://creativecommons.org/licenses/by/4.0/ | es_ES |
dc.contributor.funder | European Commission | es_ES |
dc.contributor.funder | Ministerio de Economía y Competitividad (España) | es_ES |
dc.relation.csic | Sí | es_ES |
oprm.item.hasRevision | no ko 0 false | * |
dc.identifier.funder | http://dx.doi.org/10.13039/501100000780 | es_ES |
dc.identifier.funder | http://dx.doi.org/10.13039/501100003329 | es_ES |
dc.contributor.orcid | García, José Luis [0000-0002-9238-2485] | es_ES |
dc.contributor.orcid | Nogales, Juan [0000-0002-4961-0833] | es_ES |
dc.identifier.pmid | 30423096 | - |
dc.type.coar | http://purl.org/coar/resource_type/c_6501 | es_ES |
item.languageiso639-1 | en | - |
item.fulltext | With Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
item.grantfulltext | open | - |
item.openairetype | artículo | - |
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Bioinformatics_García Jiménez_2019.pdf | Artículo principal | 796,18 kB | Adobe PDF | Visualizar/Abrir |
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