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Mission

The mission the Disease Ontology (DO) is to provide an open source ontology for the integration of biomedical data that is associated with human disease. 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 (we are working with SNOMED to see if we can release SNOMED codes linked via UMLS to the community), 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, at the end of this project, 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.

Scope

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.

Publications

Disease Ontology 2015 update: an expanded and updated database of human diseases for linking biomedical knowledge through disease data
Kibbe WA, Arze C, Felix V, Mitraka E, Bolton E, Fu G, Mungall CJ, Binder JX, Malone J, Vasant D, Parkinson H, Schriml LM.
Nucleic Acids Research 2014; Oct 27. pii: gku1011 - PDF

Disease Ontology: a backbone for disease semantic integration
Lynn Marie Schriml; Cesar Arze; Suvarna Nadendla; Yu-Wei Wayne Chang; Mark Mazaitis; Victor Felix; Gang Feng; Warren Alden Kibbe
Nucleic Acids Research 2011; doi: 10.1093/nar/gkr972 - PDF

PI's

DO Team Members

Scientific Advisory Board

Collaborators and Contributors