Providing the biomedical community with consistent, reusable and sustainable descriptions of human disease terms, phenotype characteristics and related medical vocabularies.
The Disease Ontology has been developed as a standardized ontology for human disease with the purpose of providing the biomedical community with consistent, reusable and sustainable descriptions of human disease terms, phenotype characteristics and related medical vocabulary disease concepts through collaborative efforts with biomedical researchers, coordinated by the University of Maryland School of Medicine, Institute for Genome Sciences.
The Disease Ontology semantically integrates disease and medical vocabularies through extensive cross mapping of DO terms to MeSH, ICD, NCI's thesaurus, SNOMED and OMIM.
Highlights from the DO User Community
- Performance of Gut Microbiome as an Independent Diagnostic Tool for 20 Diseases: Cross-Cohort Validation of Machine-Learning Classifiers. Li M, Liu J, Zhu J, Wang H, Sun C, Gao NL, Zhao XM, Chen WH. Gut Microbes. 2023 Jan-Dec;15(1):2205386. doi: 10.1080/19490976.2023.2205386. PMID: 37140125
- Bridging the Granularity Gap in Family History Information Extracted from Clinical Narratives. Moon S, Wang L, Chen X, Wang N, Manemann SM, Larson NB, Bielinski SJ, Liu H. AMIA Annu Symp Proc. 2023 Apr 29;2022:795-804. eCollection 2022. PMID: 37128427
- K-RET: knowledgeable biomedical relation extraction system. Sousa DF, Couto FM. Bioinformatics. 2023 Apr 3;39(4):btad174. doi: 10.1093/bioinformatics/btad174. PMID: 37018156
- Exploring FlyBase Data Using QuickSearch. Marygold SJ; FlyBase Consortium. Curr Protoc. 2023 Apr;3(4):e731. doi: 10.1002/cpz1.731. PMID: 37014762
- Prediction and curation of missing biomedical identifier mappings with Biomappings. Hoyt CT, Hoyt AL, Gyori BM. Bioinformatics. 2023 Apr 3;39(4):btad130. doi: 10.1093/bioinformatics/btad130. PMID: 36916735