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dc.contributor.author | Reyes, R. | es_ES |
dc.contributor.author | Gamermann ., Daniel | es_ES |
dc.contributor.author | Montagud Aquino, Arnau | es_ES |
dc.contributor.author | Fuente Herraiz, David | es_ES |
dc.contributor.author | Triana, J. | es_ES |
dc.contributor.author | Urchueguía Schölzel, Javier Fermín | es_ES |
dc.contributor.author | Fernández de Córdoba Castellá, Pedro José | es_ES |
dc.date.accessioned | 2014-05-28T10:35:43Z | |
dc.date.issued | 2012 | |
dc.identifier.issn | 1066-5277 | |
dc.identifier.uri | http://hdl.handle.net/10251/37840 | |
dc.description.abstract | Nowadays, the reconstruction of genome-scale metabolic models is a nonautomatized and interactive process based on decision making. This lengthy process usually requires a full year of one person¿s work in order to satisfactory collect, analyze, and validate the list of all metabolic reactions present in a specific organism. In order to write this list, one manually has to go through a huge amount of genomic, metabolomic, and physiological information. Currently, there is no optimal algorithm that allows one to automatically go through all this information and generate the models taking into account probabilistic criteria of unicity and completeness that a biologist would consider. This work presents the automation of a methodology for the reconstruction of genome-scale metabolic models for any organism. The methodology that follows is the automatized version of the steps implemented manually for the reconstruction of the genome-scale metabolic model of a photosynthetic organism, Synechocystis sp. PCC6803. The steps for the reconstruction are implemented in a computational platform (COPABI) that generates the models from the probabilistic algorithms that have been developed. For validation of the developed algorithm robustness, the metabolic models of several organisms generated by the platform have been studied together with published models that have been manually curated. Network properties of the models, like connectivity and average shortest mean path of the different models, have been compared and analyzed. | es_ES |
dc.description.sponsorship | The authors would like to thank Alberto Conejero for his useful discussions. This work has been funded by MICINN TIN2009-12359 project ArtBioCom from the Spanish Ministerio de Educacion y Ciencia. | en_EN |
dc.language | Inglés | es_ES |
dc.publisher | Mary Ann Liebert | es_ES |
dc.relation.ispartof | Journal of Computational Biology | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Genome-scale metabolic models | es_ES |
dc.subject | Networks | es_ES |
dc.subject | Connectivity | es_ES |
dc.subject.classification | FISICA APLICADA | es_ES |
dc.subject.classification | MATEMATICA APLICADA | es_ES |
dc.title | Automation on the Generation of Genome-Scale Metabolic Models | es_ES |
dc.type | Artículo | es_ES |
dc.embargo.lift | 10000-01-01 | |
dc.embargo.terms | forever | es_ES |
dc.identifier.doi | 10.1089/cmb.2012.0183 | |
dc.relation.projectID | info:eu-repo/grantAgreement/MICINN//TIN2009-12359/ES/Integracion De Bases De Datos Biologicas Con Nuevas Herramientas De Computo En Biologia Sintetica Orientadas A La Produccion De Biocombustibles/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Instituto Universitario de Matemática Pura y Aplicada - Institut Universitari de Matemàtica Pura i Aplicada | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Física Aplicada - Departament de Física Aplicada | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada | es_ES |
dc.description.bibliographicCitation | Reyes, R.; Gamermann ., D.; Montagud Aquino, A.; Fuente Herraiz, D.; Triana, J.; Urchueguía Schölzel, JF.; Fernández De Córdoba Castellá, PJ. (2012). Automation on the Generation of Genome-Scale Metabolic Models. Journal of Computational Biology. 19(12):1295-1306. https://doi.org/10.1089/cmb.2012.0183 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | http://dx.doi.org/10.1089/cmb.2012.0183 | es_ES |
dc.description.upvformatpinicio | 1295 | es_ES |
dc.description.upvformatpfin | 1306 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 19 | es_ES |
dc.description.issue | 12 | es_ES |
dc.relation.senia | 232024 | |
dc.contributor.funder | Ministerio de Ciencia e Innovación | es_ES |