Literature DB >> 18693894

Interpretation errors related to the GO annotation file format.

Dilvan A Moreira1, Nigam H Shah, Mark A Musen.   

Abstract

The Gene Ontology (GO) is the most widely used ontology for creating biomedical annotations. GO annotations are statements associating a biological entity with a GO term. These statements comprise a large dataset of biological knowledge that is used widely in biomedical research. GO Annotations are available as "gene association files" from the GO website in a tab-delimited file format (GO Annotation File Format) composed of rows of 15 tab-delimited fields. This simple format lacks the knowledge representation (KR) capabilities to represent unambiguously semantic relationships between each field. This paper demonstrates that this KR shortcoming leads users to interpret the files in ways that can be erroneous. We propose a complementary format to represent GO annotation files as knowledge bases using the W3C recommended Web Ontology Language (OWL).

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Year:  2007        PMID: 18693894      PMCID: PMC2655813     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  3 in total

1.  The Gene Ontology (GO) database and informatics resource.

Authors:  M A Harris; J Clark; A Ireland; J Lomax; M Ashburner; R Foulger; K Eilbeck; S Lewis; B Marshall; C Mungall; J Richter; G M Rubin; J A Blake; C Bult; M Dolan; H Drabkin; J T Eppig; D P Hill; L Ni; M Ringwald; R Balakrishnan; J M Cherry; K R Christie; M C Costanzo; S S Dwight; S Engel; D G Fisk; J E Hirschman; E L Hong; R S Nash; A Sethuraman; C L Theesfeld; D Botstein; K Dolinski; B Feierbach; T Berardini; S Mundodi; S Y Rhee; R Apweiler; D Barrell; E Camon; E Dimmer; V Lee; R Chisholm; P Gaudet; W Kibbe; R Kishore; E M Schwarz; P Sternberg; M Gwinn; L Hannick; J Wortman; M Berriman; V Wood; N de la Cruz; P Tonellato; P Jaiswal; T Seigfried; R White
Journal:  Nucleic Acids Res       Date:  2004-01-01       Impact factor: 16.971

2.  Ontological analysis of gene expression data: current tools, limitations, and open problems.

Authors:  Purvesh Khatri; Sorin Drăghici
Journal:  Bioinformatics       Date:  2005-06-30       Impact factor: 6.937

Review 3.  National Center for Biomedical Ontology: advancing biomedicine through structured organization of scientific knowledge.

Authors:  Daniel L Rubin; Suzanna E Lewis; Chris J Mungall; Sima Misra; Monte Westerfield; Michael Ashburner; Ida Sim; Christopher G Chute; Harold Solbrig; Margaret-Anne Storey; Barry Smith; John Day-Richter; Natalya F Noy; Mark A Musen
Journal:  OMICS       Date:  2006
  3 in total
  2 in total

1.  Genome comparison using Gene Ontology (GO) with statistical testing.

Authors:  Zhaotao Cai; Xizeng Mao; Songgang Li; Liping Wei
Journal:  BMC Bioinformatics       Date:  2006-08-11       Impact factor: 3.169

2.  FlyMine: an integrated database for Drosophila and Anopheles genomics.

Authors:  Rachel Lyne; Richard Smith; Kim Rutherford; Matthew Wakeling; Andrew Varley; Francois Guillier; Hilde Janssens; Wenyan Ji; Peter Mclaren; Philip North; Debashis Rana; Tom Riley; Julie Sullivan; Xavier Watkins; Mark Woodbridge; Kathryn Lilley; Steve Russell; Michael Ashburner; Kenji Mizuguchi; Gos Micklem
Journal:  Genome Biol       Date:  2007       Impact factor: 13.583

  2 in total

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