standards > terminology artifact > DOI:10.25504/FAIRsharing.pbbnwa

ready Orphanet Rare Diseases Ontology

Abbreviation: ORDO

General Information
Orphanet Rare Diseases Ontology (ORDO) provide a structured vocabulary for rare diseases capturing relationships between diseases, genes and other relevant features which will form a useful resource for the computational analysis of rare diseases.

How to cite this record ORDO; Orphanet Rare Diseases Ontology; DOI:; Last edited: Feb. 22, 2018, 2:06 p.m.; Last accessed: Nov 17 2018 8:24 a.m.

This record is maintained by CharlotteRodwell

Record updated: July 11, 2017, 10:44 a.m. by The FAIRsharing Team.

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Rare diseases knowledge management: the contribution of proximity measurements in OntoOrpha and OMIM.

Aime X,Charlet J,Furst F,Kuntz P,Trichet F,Dhombres F
Stud Health Technol Inform 2012

View Paper (PubMed)

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Implementing Databases (2)
Orphanet is the reference resource for information on rare diseases and orphan drugs for all publics. Its aim is to contribute to the improvement of the diagnosis, care and treatment of patients with rare diseases. Orphanet maintains the Orphanet nomenclature, essential for interoperability, and the Orphanet Rare Disease Ontology (ORDO).

DisGeNET: a database of gene-disease associations
DisGeNET is a discovery platform containing one of the largest collections available of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models, and the scientific literature, and covers the whole landscape of human diseases. The current version (v4.0) contains 429,036 associations, between 17,381 genes and 15,093 diseases, disorders and clinical or abnormal human phenotypes, and 72,870 variant-disease associations between 46,589 SNPs and 6,356 diseases and phenotypes. The data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype-phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, scripts in several programming languages, and an R package.

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