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Journal of Biomedical Informatics
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License: Elsevier Non-Commercial
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Journal of Biomedical Informatics
Article . 2008
License: Elsevier Non-Commercial
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Journal of Biomedical Informatics
Article . 2008 . Peer-reviewed
License: Elsevier Non-Commercial
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Taxonomy-based partitioning of the Gene Ontology

Authors: Wacław Kunierczyk;

Taxonomy-based partitioning of the Gene Ontology

Abstract

The Gene Ontology (GO) project is a collaborative effort to construct ontologies which facilitate biologically meaningful annotation of gene products. In some situations, only a generic or a species-specific subset of all GO terms is required to annotate and analyze the results of a particular biomedical experiment. We show that by defining explicit links between terms in the GO and terms in the Taxonomy of Species (TS) it is possible to automatically create partitions of the GO according to various taxonomic criteria. Our framework is based on three logically defined relations--validity, specificity, and relevance--used to link terms in the Gene Ontology with terms in the Taxonomy. The major advantages of this approach, as compared to the traditional GO slims methodology, are: unambiguous semantics of GO-TS annotations, significant reduction of the effort needed to manually select GO terms appropriate for a particular taxonomic context, ability to generate views of the GO even for taxa for which no explicit links with GO terms exist, logical consistency of such views, and automated updates of TS-dependent GO subsets. Incorporation of the proposed framework into the GO may improve the usability of the ontology for those scientists who focus their research on a particular species or a specific class of organisms.

Keywords

Ontology alignment, Proteome, Ontology, Annotation, Health Informatics, Classification, Computer Science Applications, Gene Ontology, Genes, Species Specificity, Terminology as Topic, Taxonomy of species, Databases, Protein, Partitioning, Taxonomy, Natural Language Processing

  • BIP!
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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    24
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
24
Top 10%
Top 10%
Top 10%
hybrid