The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
Disease Ontology 2015 update: an expanded and updated database of human diseases for linking biomedical knowledge through disease data
Open accessAbstract
The current version of the Human Disease Ontology (DO) (http://www.disease-ontology.org) database expands the utility of the ontology for the examination and comparison of genetic variation, phenotype, protein, drug and epitope data through the lens of human disease. DO is a biomedical resource of standardized common and rare disease concepts with stable identifiers organized by disease etiology. The content of DO has had 192 revisions since 2012, including the addition of 760 terms. Thirty-two percent of all terms now include definitions. DO has expanded the number and diversity of research communities and community members by 50+ during the past two years. These community members actively submit term requests, coordinate biomedical resource disease representation and provide expert curation guidance. Since the DO 2012 NAR paper, there have been hundreds of term requests and a steady increase in the number of DO listserv members, twitter followers and DO website usage. DO is moving to a multi-editor model utilizing Protégé to curate DO in web ontology language. This will enable closer collaboration with the Human Phenotype Ontology, EBI's Ontology Working Group, Mouse Genome Informatics and the Monarch Initiative among others, and enhance DO's current asserted view and multiple inferred views through reasoning.
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Cites
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Self-citationThe Human Phenotype Ontology project: linking molecular biology and disease through phenotype data
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Self-citationUberon, an integrative multi-species anatomy ontology
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Cited by
The Reactome pathway Knowledgebase
Fabregat, A., Sidiropoulos, K., Garapati, P., Gillespie, M., Hausmann, K., Haw, R., Jassal, B., Jupe, S., Korninger, F., McKay, S., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1351 · Cited by 5,605
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Pan-cancer whole-genome analyses of metastatic solid tumours
Priestley, P., Baber, J., Lolkema, M. P., Steeghs, N., de Bruijn, E., Shale, C., Duyvesteyn, K., Haidari, S., van Hoeck, A., Onstenk, W., et al. (2019) · Nature · doi:10.1038/s41586-019-1689-y · Cited by 1,106
Global hotspots and correlates of emerging zoonotic diseases
Allen, T., Murray, K. A., Zambrana-Torrelio, C., Morse, S. S., Rondinini, C., Di Marco, M., Breit, N., Olival, K. J., & Daszak, P. (2017) · Nature Communications · doi:10.1038/s41467-017-00923-8 · Cited by 1,124
Metadata
- Authors
- Kibbe, W. A., Arze, C., Felix, V., Mitraka, E., Bolton, E., Fu, G., Mungall, C. J., Binder, J. X., Malone, J., Vasant, D., Parkinson, H., & Schriml, L. M.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-10-27
- Volume
- 43
- Issue
- D1
- Pages
- D1071-D1078
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W2124045889
- Cited by
- 580
- References
- 34
- FWCI
- 20.32
- Type
- journal article
- Language
- en
- Open access
- gold
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- Kibbe, W. A., Arze, C., Felix, V., Mitraka, E., Bolton, E., Fu, G., Mungall, C. J., Binder, J. X., Malone, J., Vasant, D., Parkinson, H., & Schriml, L. M. (2015). Disease Ontology 2015 update: an expanded and updated database of human diseases for linking biomedical knowledge through disease data. Nucleic Acids Research. https://doi.org/10.1093/nar/gku1011
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
