Abstract
The current version of the Human Disease Ontology (DO) (http://www.disease-ontology.org) database expands the utility of the ontology for the examination and comparison of genetic variation, phenotype, protein, drug and epitope data through the lens of human disease. DO is a biomedical resource of standardized common and rare disease concepts with stable identifiers organized by disease etiology. The content of DO has had 192 revisions since 2012, including the addition of 760 terms. Thirty-two percent of all terms now include definitions. DO has expanded the number and diversity of research communities and community members by 50+ during the past two years. These community members actively submit term requests, coordinate biomedical resource disease representation and provide expert curation guidance. Since the DO 2012 NAR paper, there have been hundreds of term requests and a steady increase in the number of DO listserv members, twitter followers and DO website usage. DO is moving to a multi-editor model utilizing Protégé to curate DO in web ontology language. This will enable closer collaboration with the Human Phenotype Ontology, EBI's Ontology Working Group, Mouse Genome Informatics and the Monarch Initiative among others, and enhance DO's current asserted view and multiple inferred views through reasoning.
Highlights
Human disease data is a cornerstone of biomedical research for identifying drug targets, connecting genetic variations to phenotypes, understanding molecular pathways relevant to novel treatments and coupling clinical care and biomedical research [1,2]
Across the multitude of biomedical resources there is a significant need for a standardized representation of human disease to map disease concepts across resources, to connect gene variation to phenotypes and drug targets and to support development of computational tools that will enable robust data analysis and integration [3,4]
The Human Disease Ontology (Figure 1) [7] (DO, http://www.disease-ontology.org) is a community driven standards-based ontology that is focused on representing common and rare disease concepts captured across biomedical resources with the mission of providing a disease
Summary
Human disease data is a cornerstone of biomedical research for identifying drug targets, connecting genetic variations to phenotypes, understanding molecular pathways relevant to novel treatments and coupling clinical care and biomedical research [1,2]. Excluding any indirect UMLS links prevents NCI from having significant overlap with other disease vocabularies, as NCI does not provide any MeSH, OMIM or SNOMED-CT cross-references.
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