Literature DB >> 15694635

Using literature-based discovery to identify disease candidate genes.

Dimitar Hristovski1, Borut Peterlin, Joyce A Mitchell, Susanne M Humphrey.   

Abstract

We present BITOLA, an interactive literature-based biomedical discovery support system. The goal of this system is to discover new, potentially meaningful relations between a given starting concept of interest and other concepts, by mining the bibliographic database MEDLINE. To make the system more suitable for disease candidate gene discovery and to decrease the number of candidate relations, we integrate background knowledge about the chromosomal location of the starting disease as well as the chromosomal location of the candidate genes from resources such as LocusLink and Human Genome Organization (HUGO). BITOLA can also be used as an alternative way of searching the MEDLINE database. The system is available at http://www.mf.uni-lj.si/bitola/.

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Year:  2005        PMID: 15694635     DOI: 10.1016/j.ijmedinf.2004.04.024

Source DB:  PubMed          Journal:  Int J Med Inform        ISSN: 1386-5056            Impact factor:   4.046


  69 in total

1.  Exploiting semantic relations for literature-based discovery.

Authors:  Dimitar Hristovski; Carol Friedman; Thomas C Rindflesch; Borut Peterlin
Journal:  AMIA Annu Symp Proc       Date:  2006

Review 2.  Frontiers of biomedical text mining: current progress.

Authors:  Pierre Zweigenbaum; Dina Demner-Fushman; Hong Yu; Kevin B Cohen
Journal:  Brief Bioinform       Date:  2007-10-30       Impact factor: 11.622

3.  Biomedical ontologies in action: role in knowledge management, data integration and decision support.

Authors:  O Bodenreider
Journal:  Yearb Med Inform       Date:  2008

4.  A fast document classification algorithm for gene symbol disambiguation in the BITOLA literature-based discovery support system.

Authors:  Andrej Kastrin; Dimitar Hristovski
Journal:  AMIA Annu Symp Proc       Date:  2008-11-06

5.  Using the literature-based discovery paradigm to investigate drug mechanisms.

Authors:  Caroline B Ahlers; Dimitar Hristovski; Halil Kilicoglu; Thomas C Rindflesch
Journal:  AMIA Annu Symp Proc       Date:  2007-10-11

Review 6.  Candidate gene prioritization.

Authors:  Ali Masoudi-Nejad; Alireza Meshkin; Behzad Haji-Eghrari; Gholamreza Bidkhori
Journal:  Mol Genet Genomics       Date:  2012-08-15       Impact factor: 3.291

Review 7.  Recent progress in automatically extracting information from the pharmacogenomic literature.

Authors:  Yael Garten; Adrien Coulet; Russ B Altman
Journal:  Pharmacogenomics       Date:  2010-10       Impact factor: 2.533

8.  The Human Phenotype Ontology: a tool for annotating and analyzing human hereditary disease.

Authors:  Peter N Robinson; Sebastian Köhler; Sebastian Bauer; Dominik Seelow; Denise Horn; Stefan Mundlos
Journal:  Am J Hum Genet       Date:  2008-10-23       Impact factor: 11.025

9.  Comparing a Rule Based vs. Statistical System for Automatic Categorization of MEDLINE Documents According to Biomedical Specialty.

Authors:  Susanne M Humphrey; Aurélie Névéol; Julien Gobeil; Patrick Ruch; Stéfan J Darmoni; Allen Browne
Journal:  J Am Soc Inf Sci Technol       Date:  2009-12-01

10.  Discovering discovery patterns with Predication-based Semantic Indexing.

Authors:  Trevor Cohen; Dominic Widdows; Roger W Schvaneveldt; Peter Davies; Thomas C Rindflesch
Journal:  J Biomed Inform       Date:  2012-07-26       Impact factor: 6.317

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