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Nucleic Acids Res. 2019 Jan 8;47(D1):D955-D962. doi: 10.1093/nar/gky1032.

Human Disease Ontology 2018 update: classification, content and workflow expansion.

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University of Maryland School of Medicine, Institute for Genome Sciences, Baltimore, MD, USA.
Dalhousie University, Halifax, NS, Canada.
University of Maryland School of Medicine, Baltimore, MD, USA.
New York University Langone Medical Center, Department of Neurosurgery, New York, NY, USA.
Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.


The Human Disease Ontology (DO) (, 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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