» Articles » PMID: 22080554

Disease Ontology: a Backbone for Disease Semantic Integration

Overview
Specialty Biochemistry
Date 2011 Nov 15
PMID 22080554
Citations 384
Authors
Affiliations
Soon will be listed here.
Abstract

The Disease Ontology (DO) database (http://disease-ontology.org) represents a comprehensive knowledge base of 8043 inherited, developmental and acquired human diseases (DO version 3, revision 2510). The DO web browser has been designed for speed, efficiency and robustness through the use of a graph database. Full-text contextual searching functionality using Lucene allows the querying of name, synonym, definition, DOID and cross-reference (xrefs) with complex Boolean search strings. The DO semantically integrates disease and medical vocabularies through extensive cross mapping and integration of MeSH, ICD, NCI's thesaurus, SNOMED CT and OMIM disease-specific terms and identifiers. The DO is utilized for disease annotation by major biomedical databases (e.g. Array Express, NIF, IEDB), as a standard representation of human disease in biomedical ontologies (e.g. IDO, Cell line ontology, NIFSTD ontology, Experimental Factor Ontology, Influenza Ontology), and as an ontological cross mappings resource between DO, MeSH and OMIM (e.g. GeneWiki). The DO project (http://diseaseontology.sf.net) has been incorporated into open source tools (e.g. Gene Answers, FunDO) to connect gene and disease biomedical data through the lens of human disease. The next iteration of the DO web browser will integrate DO's extended relations and logical definition representation along with these biomedical resource cross-mappings.

Citing Articles

A Multi-Omics-Based Exploration of the Predictive Role of MSMB in Prostate Cancer Recurrence: A Study Using Bayesian Inverse Convolution and 10 Machine Learning Combinations.

Huang S, Yin H Biomedicines. 2025; 13(2).

PMID: 40002900 PMC: 11853722. DOI: 10.3390/biomedicines13020487.


Mapping naturally presented T cell antigens in medulloblastoma based on integrative multi-omics.

Velz J, Freudenmann L, Medici G, Dubbelaar M, Mohme M, Ghasemi D Nat Commun. 2025; 16(1):1364.

PMID: 39904979 PMC: 11794601. DOI: 10.1038/s41467-025-56268-0.


Comprehensive evaluation of pure and hybrid collaborative filtering in drug repurposing.

Reda C, Vie J, Wolkenhauer O Sci Rep. 2025; 15(1):2711.

PMID: 39837888 PMC: 11751339. DOI: 10.1038/s41598-025-85927-x.


A genome-wide association study of high-sensitivity C-reactive protein in a large Korean population highlights its genetic relationship with cholesterol metabolism.

Oh K, Yuk M, Yang S, Youn J, Dong Q, Wang Z Sci Rep. 2025; 15(1):189.

PMID: 39747571 PMC: 11696572. DOI: 10.1038/s41598-024-84466-1.


BioMedGraphica: An All-in-One Platform for Biomedical Prior Knowledge and Omic Signaling Graph Generation.

Zhang H, Liang S, Xu T, Li W, Huang D, Dong Y bioRxiv. 2024; .

PMID: 39713411 PMC: 11661111. DOI: 10.1101/2024.12.05.627020.


References
1.
Osborne J, Lin S, Zhu L, Kibbe W . Mining biomedical data using MetaMap Transfer (MMtx) and the Unified Medical Language System (UMLS). Methods Mol Biol. 2008; 408:153-69. DOI: 10.1007/978-1-59745-547-3_9. View

2.
Osborne J, Flatow J, Holko M, Lin S, Kibbe W, Zhu L . Annotating the human genome with Disease Ontology. BMC Genomics. 2009; 10 Suppl 1:S6. PMC: 2709267. DOI: 10.1186/1471-2164-10-S1-S6. View

3.
Jonquet C, Musen M, Shah N . Building a biomedical ontology recommender web service. J Biomed Semantics. 2010; 1 Suppl 1:S1. PMC: 2903720. DOI: 10.1186/2041-1480-1-S1-S1. View

4.
Huss 3rd J, Lindenbaum P, Martone M, Roberts D, Pizarro A, Valafar F . The Gene Wiki: community intelligence applied to human gene annotation. Nucleic Acids Res. 2009; 38(Database issue):D633-9. PMC: 2808918. DOI: 10.1093/nar/gkp760. View

5.
Nelson S, Schopen M, Savage A, Schulman J, Arluk N . The MeSH translation maintenance system: structure, interface design, and implementation. Stud Health Technol Inform. 2004; 107(Pt 1):67-9. View