2 datasets found
  1. b

    Gene Ontology Annotation Database

    • bioregistry.io
    Updated Apr 24, 2021
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    (2021). Gene Ontology Annotation Database [Dataset]. https://bioregistry.io/goa
    Explore at:
    Dataset updated
    Apr 24, 2021
    Description

    The GOA (Gene Ontology Annotation) project provides high-quality Gene Ontology (GO) annotations to proteins in the UniProt Knowledgebase (UniProtKB) and International Protein Index (IPI). This involves electronic annotation and the integration of high-quality manual GO annotation from all GO Consortium model organism groups and specialist groups.

  2. w

    Bio2RDF::GOA

    • data.wu.ac.at
    api/sparql +2
    Updated May 15, 2014
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    (2014). Bio2RDF::GOA [Dataset]. https://data.wu.ac.at/odso/linkeddatacatalog_dws_informatik_uni-mannheim_de/YzNlNTFiYjYtNzJkMC00ODRlLWFhMGQtNjgyNDA4M2NkZWVi
    Explore at:
    application/n-triples, api/sparql, htmlAvailable download formats
    Dataset updated
    May 15, 2014
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The GOA (Gene Ontology Annotation) project provides high-quality Gene Ontology (GO) annotations to proteins in the UniProt Knowledgebase (UniProtKB) and International Protein Index (IPI). This involves electronic annotation and the integration of high-quality manual GO annotation from all GO Consortium model organism groups and specialist groups.

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Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
(2021). Gene Ontology Annotation Database [Dataset]. https://bioregistry.io/goa

Gene Ontology Annotation Database

Explore at:
420 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Apr 24, 2021
Description

The GOA (Gene Ontology Annotation) project provides high-quality Gene Ontology (GO) annotations to proteins in the UniProt Knowledgebase (UniProtKB) and International Protein Index (IPI). This involves electronic annotation and the integration of high-quality manual GO annotation from all GO Consortium model organism groups and specialist groups.

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