Show simple item record

dc.contributor.authorUsié Chimenos, Anabel
dc.contributor.authorKarathia, Hiren
dc.contributor.authorTeixidó Torrelles, Ivan
dc.contributor.authorAlves, Rui
dc.contributor.authorSolsona Tehàs, Francesc
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.relation.isformatofReproducció del document publicat a
dc.relation.ispartofPeerJ, 2014, núm. 2, pàg. 276-289ca_ES
dc.rightscc-by, (c) Usié et al., 2014ca_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

Files in this item


This item appears in the following Collection(s)

Show simple item record

cc-by, (c) Usié et al., 2014
Except where otherwise noted, this item's license is described as cc-by, (c) Usié et al., 2014