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dc.contributor.authorUsié Chimenos, Anabel
dc.contributor.authorKarathia, Hiren
dc.contributor.authorTeixidó Torrelles, Ivan
dc.contributor.authorValls Marsal, Joan
dc.contributor.authorFaus i Torà, Xavier
dc.contributor.authorAlves, Rui
dc.contributor.authorSolsona Tehàs, Francesc
dc.date.accessioned2012-06-15T12:28:56Z
dc.date.available2012-06-15T12:28:56Z
dc.date.issued2011
dc.identifier.issn1471-2105
dc.identifier.urihttp://hdl.handle.net/10459.1/45586
dc.description.abstractBackground: Reconstruction of genes and/or protein networks from automated analysis of the literature is one of the current targets of text mining in biomedical research. Some user-friendly tools already perform this analysis on precompiled databases of abstracts of scientific papers. Other tools allow expert users to elaborate and analyze the full content of a corpus of scientific documents. However, to our knowledge, no user friendly tool that simultaneously analyzes the latest set of scientific documents available on line and reconstructs the set of genes referenced in those documents is available. Results: This article presents such a tool, Biblio-MetReS, and compares its functioning and results to those of other user-friendly applications (iHOP, STRING) that are widely used. Under similar conditions, Biblio-MetReS creates networks that are comparable to those of other user friendly tools. Furthermore, analysis of full text documents provides more complete reconstructions than those that result from using only the abstract of the document. Conclusions: Literature-based automated network reconstruction is still far from providing complete reconstructions of molecular networks. However, its value as an auxiliary tool is high and it will increase as standards for reporting biological entities and relationships become more widely accepted and enforced. Biblio- MetReS is an application that can be downloaded from http://metres.udl.cat/. It provides an easy to use environment for researchers to reconstruct their networks of interest from an always up to date set of scientific documents.ca_ES
dc.description.sponsorshipRA was partially supported by the Ministerio de Ciencia e Innovación (MICINN, Spain through grants BFU2007-62772/BMC and BFU2010-17704), and by the FLAD foundation. FS was partially funded by the MICINN, with grants TIN2008-05913 and CSD-2007-00050. The authors are members of the research groups 2009SGR809 and 2009SGR145, funded by the "Generalitat de Catalunya". HK is funded by a Generalitat de Catalunya (AGAUR) Ph. D. fellowship. AU is funded by a Universitat de Lleida Ph. D. fellowship. We thank David Terés for assistance in programming parts of the application. We also thank two anonymous reviewers for suggestion and criticism that made this work better.
dc.language.isoengca_ES
dc.publisherBioMed Centralca_ES
dc.relationMIECI/PN2004-2007/BFU2007-62772/BMC
dc.relationMICINN/PN2008-2011/BFU2010-17704
dc.relationMICINN/PN2008-2011/TIN2008-05913
dc.relationMIECI/PN2004-2007/CSD-2007-00050
dc.relation.isformatofReproducció del document publicat a https://doi.org/10.1186/1471-2105-12-387ca_ES
dc.relation.ispartofBMC Bioinformatics, 2011, vol. 12, núm. 387, p. 1-10ca_ES
dc.rightscc-by, (c) Usié et al., 2011ca_ES
dc.rights.urihttp://creativecommons.org/licenses/by/2.0/es/deed.caca_ES
dc.subject.otherMineria de dadesca_ES
dc.subject.otherBases de dadesca_ES
dc.titleBiblio-MetReS: A bibliometric network reconstruction application and serverca_ES
dc.typearticleca_ES
dc.identifier.idgrec020995
dc.type.versionpublishedVersionca_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.identifier.doihttps://doi.org/10.1186/1471-2105-12-387


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cc-by, (c) Usié et al., 2011
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