Literature DB >> 12463875

The lexical properties of the gene ontology.

Alexa T McCray1, Allen C Browne, Olivier Bodenreider.   

Abstract

The Gene Ontology (GO) is a construct developed for the purpose of annotating molecular information about genes and their products. The ontology is a shared resource developed by the GO Consortium, a group of scientists who work on a variety of model organisms. In this paper we investigate the nature of the strings found in the Gene Ontology and evaluate them for their usefulness in natural language processing (NLP). We extend previous work that identified a set of properties that reliably identifies natural language phrases in the Unified Medical Language System (UMLS). The results indicate that a large percentage (79%) of GO terms are potentially useful for NLP applications. Some 35% of the GO terms were found in a corpus derived from the MEDLINE bibliographic database, and 27% of the terms were found in the current edition of the UMLS.

Mesh:

Year:  2002        PMID: 12463875      PMCID: PMC2244431     

Source DB:  PubMed          Journal:  Proc AMIA Symp        ISSN: 1531-605X


  7 in total

1.  A knowledge model for analysis and simulation of regulatory networks.

Authors:  A Rzhetsky; T Koike; S Kalachikov; S M Gomez; M Krauthammer; S H Kaplan; P Kra; J J Russo; C Friedman
Journal:  Bioinformatics       Date:  2000-12       Impact factor: 6.937

Review 2.  Ontology-based knowledge representation for bioinformatics.

Authors:  R Stevens; C A Goble; S Bechhofer
Journal:  Brief Bioinform       Date:  2000-11       Impact factor: 11.622

3.  Evaluating UMLS strings for natural language processing.

Authors:  A T McCray; O Bodenreider; J D Malley; A C Browne
Journal:  Proc AMIA Symp       Date:  2001

4.  Creating the gene ontology resource: design and implementation.

Authors: 
Journal:  Genome Res       Date:  2001-08       Impact factor: 9.043

5.  Saccharomyces Genome Database (SGD) provides secondary gene annotation using the Gene Ontology (GO).

Authors:  Selina S Dwight; Midori A Harris; Kara Dolinski; Catherine A Ball; Gail Binkley; Karen R Christie; Dianna G Fisk; Laurie Issel-Tarver; Mark Schroeder; Gavin Sherlock; Anand Sethuraman; Shuai Weng; David Botstein; J Michael Cherry
Journal:  Nucleic Acids Res       Date:  2002-01-01       Impact factor: 16.971

Review 6.  The nature of lexical knowledge.

Authors:  A T McCray
Journal:  Methods Inf Med       Date:  1998-11       Impact factor: 2.176

Review 7.  How knowledge drives understanding--matching medical ontologies with the needs of medical language processing.

Authors:  U Hahn; M Romacker; S Schulz
Journal:  Artif Intell Med       Date:  1999-01       Impact factor: 5.326

  7 in total
  11 in total

1.  Linking biomedical language information and knowledge resources: GO and UMLS.

Authors:  I N Sarkar; M N Cantor; R Gelman; F Hartel; Y A Lussier
Journal:  Pac Symp Biocomput       Date:  2003

2.  The compositional structure of Gene Ontology terms.

Authors:  P V Ogren; K B Cohen; G K Acquaah-Mensah; J Eberlein; L Hunter
Journal:  Pac Symp Biocomput       Date:  2004

Review 3.  Interface terminologies: facilitating direct entry of clinical data into electronic health record systems.

Authors:  S Trent Rosenbloom; Randolph A Miller; Kevin B Johnson; Peter L Elkin; Steven H Brown
Journal:  J Am Med Inform Assoc       Date:  2006-02-24       Impact factor: 4.497

4.  Rewriting and suppressing UMLS terms for improved biomedical term identification.

Authors:  Kristina M Hettne; Erik M van Mulligen; Martijn J Schuemie; Bob Ja Schijvenaars; Jan A Kors
Journal:  J Biomed Semantics       Date:  2010-03-31

5.  Translational systems genomics: ontology and imaging.

Authors:  Su-Shing Chen; Yu-Ping Wang
Journal:  Summit Transl Bioinform       Date:  2009-03-01

6.  War of ontology worlds: mathematics, computer code, or Esperanto?

Authors:  Andrey Rzhetsky; James A Evans
Journal:  PLoS Comput Biol       Date:  2011-09-29       Impact factor: 4.475

7.  How to link ontologies and protein-protein interactions to literature: text-mining approaches and the BioCreative experience.

Authors:  Martin Krallinger; Florian Leitner; Miguel Vazquez; David Salgado; Christophe Marcelle; Mike Tyers; Alfonso Valencia; Andrew Chatr-aryamontri
Journal:  Database (Oxford)       Date:  2012-03-21       Impact factor: 3.451

8.  A sentence sliding window approach to extract protein annotations from biomedical articles.

Authors:  Martin Krallinger; Maria Padron; Alfonso Valencia
Journal:  BMC Bioinformatics       Date:  2005-05-24       Impact factor: 3.169

9.  Mining protein function from text using term-based support vector machines.

Authors:  Simon B Rice; Goran Nenadic; Benjamin J Stapley
Journal:  BMC Bioinformatics       Date:  2005-05-24       Impact factor: 3.169

10.  Mapping the gene ontology into the unified medical language system.

Authors:  Jane Lomax; Alexa T McCray
Journal:  Comp Funct Genomics       Date:  2004
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