Abstract
The Disease Ontology (DO) enables cross-domain data integration through a common standard of human disease terms and their etiological descriptions. Standardized disease descriptors that are integrated across mammalian genomic resources provide a human-readable, machine-interpretable, community-driven disease corpus that unifies the representation of human common and rare diseases. The DO is populated by consensus-driven disease data descriptors that incorporate disease terms utilized by genomic and genetic projects and resources engaged in studies to understand the genetics of human disease through the study of model organisms. The DO project serves multiple roles for the model organism community by providing: (1) a structured “backbone” of disease concepts represented among the model organism databases; (2) authoritative disease curation services to researchers and resource providers; and (3) development of subsets of the DO representative of human diseases annotated to animal models curated within the model organism databases.
Highlights
The nomenclature of human disease has a long and complex history
The Disease Ontology (DO) is populated by consensus-driven disease data descriptors that incorporate disease terms utilized by genomic and genetic projects and resources engaged in studies to understand the genetics of human disease through the study of model organisms
The DO project serves multiple roles for the model organism community by providing: (1) a structured ‘‘backbone’’ of disease concepts represented among the model organism databases; (2) authoritative disease curation services to researchers and resource providers; and (3) development of subsets of the DO representative of human diseases annotated to animal models curated within the model organism databases
Summary
The nomenclature of human disease has a long and complex history. Traditionally, diseases have been named for the discoverer of the disease (Robinow syndrome), where the disease was first discovered (Rocky Mountain spotted fever), or the animal in which the disease was first identified (avian influenza). There is a significant need for a standardized representation of human diseases to map disease concepts across resources, to connect related information, and to support the development of computational tools that will enable robust data analysis and integration.
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