The Human Disease Ontology 2022 update

Abstract The Human Disease Ontology (DO) (www.disease-ontology.org) database, has significantly expanded the disease content and enhanced our userbase and website since the DO’s 2018 Nucleic Acids Research DATABASE issue paper. Conservatively, based on available resource statistics, terms from the D...

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Veröffentlicht in:Nucleic acids research 2022-01, Vol.50 (D1), p.D1255-D1261
Hauptverfasser: Schriml, Lynn M, Munro, James B, Schor, Mike, Olley, Dustin, McCracken, Carrie, Felix, Victor, Baron, J Allen, Jackson, Rebecca, Bello, Susan M, Bearer, Cynthia, Lichenstein, Richard, Bisordi, Katharine, Dialo, Nicole Campion, Giglio, Michelle, Greene, Carol
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Sprache:eng
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Zusammenfassung:Abstract The Human Disease Ontology (DO) (www.disease-ontology.org) database, has significantly expanded the disease content and enhanced our userbase and website since the DO’s 2018 Nucleic Acids Research DATABASE issue paper. Conservatively, based on available resource statistics, terms from the DO have been annotated to over 1.5 million biomedical data elements and citations, a 10× increase in the past 5 years. The DO, funded as a NHGRI Genomic Resource, plays a key role in disease knowledge organization, representation, and standardization, serving as a reference framework for multiscale biomedical data integration and analysis across thousands of clinical, biomedical and computational research projects and genomic resources around the world. This update reports on the addition of 1,793 new disease terms, a 14% increase of textual definitions and the integration of 22 137 new SubClassOf axioms defining disease to disease connections representing the DO’s complex disease classification. The DO’s updated website provides multifaceted etiology searching, enhanced documentation and educational resources. Graphical Abstract Graphical Abstract The Human Disease Ontology (DO) integrates disease features and etiological factors to describe disease complexity. The DO is extensively cited and integrated into highly cited databases.
ISSN:0305-1048
1362-4962
DOI:10.1093/nar/gkab1063