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Home > About > The Disease Ontology Project

The Disease Ontology Knowledgebase (DO-KB) provides access for exploring integrated disease mechanism and feature knowledge, semantically-defined within the Human Disease Ontology, serving as a reference framework for multiscale biomedical data integration and analysis within a unifying etiology-based disease classification.

The Disease Ontology Knowledgebase (DO-KB) is recognized as a Global Core Biodata Resource.


The mission of the Disease Ontology (DO) is to provide an open-source ontology that serves as a genomic resource for the integration of biomedical data associated with human disease, disease features and mechanisms; ultimately, serving as a reference framework for multiscale biomedical data integration and analysis towards strengthening the disease information ecosystem. DO will have a formally correct (in the ontology sense), semantically computable structure. Terms in DO will be well defined, using standard references. These terms will be linked to well-established, well-adopted terminologies that contain disease and disease-related concepts such as SNOMED, ICD-9 and ICD-10, MeSH, and UMLS. The combination of a semantically computable structure and the external references to these terminologies will enable useful inference between disparate datasets using one or more of these standard terminologies to code disease. The Disease Ontology will be a community-driven, community-accepted ontology of diseases for clinical research and medicine inclusive of genetic, environmental and infectious diseases. The Disease Ontology will encapsulate, therefore, a comprehensive theory of disease. The design of the disease ontology will enable greater understanding of disease states by placing heritable disorders in the context of other infectious diseases and related diseases. The structure of Disease Ontology and the external references to other terminologies will enable the integration of disparate datasets through the concept of disease.


The Disease Ontology is a community driven, open source ontology that is designed to link disparate datasets through disease concepts. We will provide a computable structure of inheritable, environmental and infectious origins of human disease to facilitate the connection of genetic data, clinical data, and symptoms through the lens of human disease. We hope and anticipate that this will be useful for coupling disease concepts in model organisms to human disease concepts. The Disease Ontology should enable the cross-walk between disease concepts, genes contributing to disease, and the 'cloud' of associated symptoms, findings and signs. The use of the disease ontology requires these connections to be done through evidence-based associations. Our understanding of disease, and the association of disease with phenotype, environment, and genetics is dynamic and a reflection of current knowledge. The Disease Ontology is currently under review as part of the OBO Foundry review process.


The Disease Ontology is a project of the University of Maryland School of Medicine, Institute for Genome Sciences at 670 West Baltimore St, Baltimore, MD 21201.


The principle investigator for the Disease Ontology is Lynn Schriml.


The data produced by the Human Disease Ontology project is published from the United States under the CC0 1.0 Universal license and, to the extent possible under law, is dedicated to the public domain.


Current Funding

09/06/2022 – 06/30/2027 NIH/NHGRI 1U24HG012557-01
NHGRI Biomedical Knowledgebase
The Human Disease Ontology: An integrated, mechanistic knowledge resource for biomedical research.

09/14/2017 - 06/30/2024 NIH/NHGRI U41 HG008735-01A1
NHGRI Genome Resource
The Disease Ontology Project: Mechanistic profiles of human disease for biomedical and clinical research.

Prior Funding

07/15/2014 – 04/30/2022 NIH/NIGMS 2R01GM089820-10
Gene Wiki: A community-maintained knowledge base of biomedical information.

03/01/2015 - 03/31/2017 NIH-NHGRI U41 (BD2K) Administrative Supplemental 2U41HG000330-28
Harmonizing Disease Annotation of Mouse and Rat Models through the Human Disease Ontology.

7/16/2009 - 06/30/2012 NIH-NCRR ARRA NIH-R01 RR025342
Disease Ontology: An Open Biomedical Ontology for Disease.