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dc.contributor.authorUsié Chimenos, Anabel
dc.contributor.authorKarathia, Hiren
dc.contributor.authorTeixidó Torrelles, Ivan
dc.contributor.authorAlves, Rui
dc.contributor.authorSolsona Tehàs, Francesc
dc.date.accessioned2015-06-04T11:01:51Z
dc.date.available2015-06-04T11:01:51Z
dc.date.issued2014
dc.identifier.issn2167-8359
dc.identifier.urihttp://hdl.handle.net/10459.1/48308
dc.description.abstractOne way to initiate the reconstruction of molecular circuits is by using automated text-mining techniques. Developing more efficient methods for such reconstruction is a topic of active research, and those methods are typically included by bioinfor- maticians in pipelines used to mine and curate large literature datasets. Nevertheless, experimental biologists have a limited number of available user-friendly tools that use text-mining for network reconstruction and require no programming skills to use. One of these tools is Biblio-MetReS. Originally, this tool permitted an on-the-fly analysis of documents contained in a number of web-based literature databases to identify co-occurrence of proteins/genes. This approach ensured results that were always up-to-date with the latest live version of the databases. However, this `up-to- dateness' came at the cost of large execution times. Here we report an evolution of the application Biblio-MetReS that permits constructing co-occurrence networks for genes, GO processes, Pathways, or any combination of the three types of entities and graphically represent those entities.We show that the performance of Biblio- MetReS in identifying gene co-occurrence is as least as good as that of other com- parable applications (STRING and iHOP). In addition, we also show that the iden- tification of GO processes is on par to that reported in the latest BioCreAtIvE chal- lenge. Finally, we also report the implementation of a new strategy that combines on-the-fly analysis of new documents with preprocessed information from docu- ments that were encountered in previous analyses. This combination simultaneously decreases program run time and maintains `up-to-dateness' of the results.ca_ES
dc.description.sponsorshipRA was partially supported by the Ministerio de Ciencia e Innovación (MICINN, Spain through grant BFU2010-17704). FS was partially funded by the MICINN, with grants TIN2011-28689-C02-02. The authors are members of the research groups 2009SGR809 and 2009SGR145, funded by the “Generalitat de Catalunya”. AU is funded by a Generalitat de Catalunya (AGAUR) PhD fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
dc.language.isoengca_ES
dc.publisherPeerJca_ES
dc.relationMICINN/PN2008-2011/BFU2010-17704
dc.relationMICINN/PN2008-2011/TIN2011-28689-C02-02
dc.relation.isformatofReproducció del document publicat a https://doi.org/10.7717/peerj.276ca_ES
dc.relation.ispartofPeerJ, 2014, núm. 2, pàg. 276-289ca_ES
dc.rightscc-by, (c) Usié et al., 2014ca_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectNetwork reconstructionca_ES
dc.subjectSystems biologyca_ES
dc.subjectLiterature analysisca_ES
dc.titleBiblio-MetReS for user-friendly mining of genes and biological processes in scientific documentsca_ES
dc.typearticleca_ES
dc.identifier.idgrec020715
dc.type.versionpublishedVersionca_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_ES
dc.identifier.doihttps://doi.org/10.7717/peerj.276


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