Human Disease Ontology

By Lynn Schriml

University of Maryland, Baltimore

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Abstract

The Disease Ontology has been developed as a standardized ontology for human disease, since 2003, with the purpose of providing the biomedical community with manual curated, consistent, reusable and sustainable descriptions of human disease terms, phenotype characteristics and related medical vocabulary disease concepts. 

The Disease Ontology provides a standardized ontological classification of cancers, benign neoplasms and pre-malignant neoplasms.  The cancer branch is further subdivided into cell type cancer and organ system cancer.  The Disease Ontology project provides a DO_cancer_slim which unifies the representation of cancer terms across cancer mutation databases  (COSMIC, TCGA, ICGC, TARGET, IntOGen and EDRN) as a cohesive set of DO terms and enables cross-databases cancer analyses. 

The Disease Ontology builds a clear hierarchical and structural relationship between disease terms and concepts, and it semantically integrates MeSH, OMIM, ICD-9-CM, ICD-10, NCI thesaurus, Orphanet, NORD, UMLS and SNOMED CT terms and IDs together through extensive cross mapping of concepts represented in the Disease Ontology's cross-reference section. 

 

References

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

Publications

Wu, T.-J., Schriml, L.M., Chen, Q.-R., Colbert, M., Crichton, D. J., Finney, R., Hu, Y., Kibbe, W. A., Kincaid, H., Meerzaman, D., Mitraka, E., Pan, Y., Smith, K. M., Srivastava, S., Ward, S., Yan, C. and Mazumder, R. (2015) Generating a focused view of disease ontology cancer terms for pan-cancer data integration and analysis. Database, 2015, bav032.

Cite this work

Researchers should cite this work as follows:

  • Lynn Schriml (2016), "Human Disease Ontology," https://ncihub.org/resources/1838.

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