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Biblio-MetReS: A bibliometric network reconstruction application and server

Anabel Usié1,2, Hiren Karathia2, Ivan Teixidó1, Joan Valls2, Xavier Faus1, Rui Alves2* and Francesc Solsona1*

Author Affiliations

1 Department d'Informàtica i Enginyeria Industrial, Universitat de Lleida, Av. Jaume II n°69, 25001 Lleida, Spain

2 Department de Ciències Mèdiques Bàsiques & IRBLleida, Universitat de Lleida, Montserrat Roig n°2, 25008 Lleida, Spain

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BMC Bioinformatics 2011, 12:387 doi:10.1186/1471-2105-12-387

Published: 5 October 2011

Abstract

Background

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/ webcite. 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.