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Human Disease Ontology 2018 Update: Classification, Content and Workflow Expansion

Abstract

The Human Disease Ontology (DO) (http://www.disease-ontology.org), database has undergone significant expansion in the past three years. The DO disease classification includes specific formal semantic rules to express meaningful disease models and has expanded from a single asserted classification to include multiple-inferred mechanistic disease classifications, thus providing novel perspectives on related diseases. Expansion of disease terms, alternative anatomy, cell type and genetic disease classifications and workflow automation highlight the updates for the DO since 2015. The enhanced breadth and depth of the DO's knowledgebase has expanded the DO's utility for exploring the multi-etiology of human disease, thus improving the capture and communication of health-related data across biomedical databases, bioinformatics tools, genomic and cancer resources and demonstrated by a 6.6× growth in DO's user community since 2015. The DO's continual integration of human disease knowledge, evidenced by the more than 200 SVN/GitHub releases/revisions, since previously reported in our DO 2015 NAR paper, includes the addition of 2650 new disease terms, a 30% increase of textual definitions, and an expanding suite of disease classification hierarchies constructed through defined logical axioms.

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References
1.
Nelson S, Schopen M, Savage A, Schulman J, Arluk N . The MeSH translation maintenance system: structure, interface design, and implementation. Stud Health Technol Inform. 2004; 107(Pt 1):67-9. View

2.
Smith B, Ceusters W, Klagges B, Kohler J, Kumar A, Lomax J . Relations in biomedical ontologies. Genome Biol. 2005; 6(5):R46. PMC: 1175958. DOI: 10.1186/gb-2005-6-5-r46. View

3.
Donnelly K . SNOMED-CT: The advanced terminology and coding system for eHealth. Stud Health Technol Inform. 2006; 121:279-90. View

4.
Smith B, Ashburner M, Rosse C, Bard J, Bug W, Ceusters W . The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol. 2007; 25(11):1251-5. PMC: 2814061. DOI: 10.1038/nbt1346. View

5.
de Coronado S, Wright L, Fragoso G, Haber M, Hahn-Dantona E, Hartel F . The NCI Thesaurus quality assurance life cycle. J Biomed Inform. 2009; 42(3):530-9. DOI: 10.1016/j.jbi.2009.01.003. View