Disease Ontology: a backbone for disease semantic integration
Open accessAbstract
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.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The Disease Ontology data were further extended and newer ontologies such as Rat Disease Ontology and Mammalian Phenotype Ontology were added to facilitate comparison of target-disease and target-phenotype associations across multiple species.
“The Disease Ontology (DO) (8) data were further extended and newer ontologies such as Rat Disease Ontology (9) and Mammalian Phenotype Ontology (10) were added to facilitate comparison of target-disease and target-phenotype associations across multiple species.”
From TCRD and pharos 2021: mining the human proteome for disease biology (2021) · cites this paper as [8]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Database resources of the National Center for Biotechnology Information: update
Wheeler, D. L. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkh073 · Cited by 10,691 · see citing works
A reference ontology for biomedical informatics: the Foundational Model of Anatomy
Rosse, C., & Mejino, J. L. (2003) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2003.11.007 · Cited by 1,167 · see citing works
Relations in biomedical ontologies
Smith, B., Ceusters, W. M., Klagges, B. R. E., Köhler, J., Kumar, A., Lomax, J., Mungall, C., Neuhaus, F., Rector, A. L., & Rosse, C. (2005) · Genome biology · doi:10.1186/gb-2005-6-5-r46 · Cited by 1,030 · see citing works
Database resources of the National Center for Biotechnology Information
Sayers, E. W., Barrett, T., Benson, D. A., Bryant, S. H., Canese, K., Chetvernin, V., Church, D. M., DiCuccio, M. N., Edgar, R., Federhen, S., et al. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn741 · Cited by 767 · see citing works
The immune epitope database 2.0
Vita, R., Zarebski, L., Greenbaum, J. A., Emami, H., Hoof, I., Salimi, N., Damle, R., Sette, A., & Peters, B. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkp1004 · Cited by 631 · see citing works
The Gene Ontology in 2010: extensions and refinements
The Gene Ontology Consortium (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp1018 · Cited by 462 · see citing works
Immunity and other defenses in pea aphids, Acyrthosiphon pisum
Gerardo, N. M., Altincicek, B., Anselme, C., Atamian, H. S., Barribeau, S. M., de Vos, M., Duncan, E. J., Evans, J. D., Gabaldón, T., Ghanim, M., et al. (2010) · Genome biology · doi:10.1186/gb-2010-11-2-r21 · Cited by 447 · see citing works
NCI Thesaurus: A semantic model integrating cancer-related clinical and molecular information
Sioutos, N., de Coronado, S., Haber, M. W., Hartel, F. W., Shaiu, W.-L., & Wright, L. W. (2006) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2006.02.013 · Cited by 444 · see citing works
Robinson, P. N., & Mundlos, S. (2010) · Clinical Genetics · doi:10.1111/j.1399-0004.2010.01436.x · Cited by 357 · see citing works
Parkinson, H., Sarkans, U., Kolesnikov, N. N., Abeygunawardena, N., Burdett, T., Dyląg, M., Emam, I., Farne, A., Hastings, E., Holloway, E., et al. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq1040 · Cited by 337 · see citing works
A new face and new challenges for Online Mendelian Inheritance in Man (OMIM®)
Amberger, J. S., Bocchini, C. A., & Hamosh, A. (2011) · Human Mutation · doi:10.1002/humu.21466 · Cited by 332 · see citing works
Integrating phenotype ontologies across multiple species
Mungall, C., Gkoutos, G. V., Smith, C. L., Haendel, M. A., Lewis, S. E., & Ashburner, M. (2010) · Genome biology · doi:10.1186/gb-2010-11-1-r2 · Cited by 284 · see citing works
Annotating the human genome with Disease Ontology
Osborne, J. D., Flatow, J. M., Holko, M., Lin, S. M., Kibbe, W. A., Zhu, L. J., Danila, M. I., Feng, G., & Chisholm, R. L. (2009) · BMC Genomics · doi:10.1186/1471-2164-10-s1-s6 · Cited by 265 · see citing works
Self-citationThe Ontology Lookup Service, a lightweight cross-platform tool for controlled vocabulary queries
Côté, R. G., JONES, P. M., Apweiler, R., et al. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-97 · Cited by 224 · see citing works
The Ascension of Wildlife Rabies: A Cause for Public Health Concern or Intervention?
Rupprecht, C. E., Smith, J. S., Fekadu, M., et al. (1995) · Emerging infectious diseases · doi:10.3201/eid0104.950401 · Cited by 212 · see citing works
Toward an ontological treatment of disease and diagnosis.
Scheuermann, R. H., Ceusters, W. M., & Smith, B. (2009) · PubMed · Cited by 200 · see citing works
The NIFSTD and BIRNLex Vocabularies: Building Comprehensive Ontologies for Neuroscience
Bug, W. J., Ascoli, G. A., Grethe, J. S., Gupta, A., Fennema‐Notestine, C., Laird, A. R., Larson, S., Rubin, D. L., Shepherd, G. M., Turner, J. A., et al. (2008) · Neuroinformatics · doi:10.1007/s12021-008-9032-z · Cited by 157 · see citing works
The Rat Genome Database, update 2007--Easing the path from disease to data and back again
Twigger, S. N., Shimoyama, M. E., Bromberg, S. K., Kwitek, A. E., Jacob, H. J., & the RGD Team (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl988 · Cited by 132 · see citing works
The MeSH Translation Maintenance System: Structure, Interface Design, and Implementation
Nelson, S. J., Schopen, M., Savage, A. G., Schulman, J.-L., & Arluk, N. (2004) · Studies in health technology and informatics · doi:10.3233/978-1-60750-949-3-67 · Cited by 131 · see citing works
Du, P., Feng, G., Flatow, J. M., Song, J. Y., Holko, M., Kibbe, W. A., & Lin, S. M. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp193 · Cited by 109 · see citing works
Self-citationThe Gene Wiki: community intelligence applied to human gene annotation
Huss, J. W., Lindenbaum, P., Martone, M. F., Roberts, D., Pizarro, A., Valafar, F., Hogenesch, J. B., & Su, A. I. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp760 · Cited by 79 · see citing works
Foundations for a realist ontology of mental disease
Ceusters, W. M., & Smith, B. (2010) · Journal of Biomedical Semantics · doi:10.1186/2041-1480-1-10 · Cited by 78 · see citing works
Building a biomedical ontology recommender web service
Jonquet, C., Musen, M. A., & Shah, N. H. (2010) · Journal of Biomedical Semantics · doi:10.1186/2041-1480-1-s1-s1 · Cited by 74 · see citing works
A collection of bioconductor methods to visualize gene-list annotations
Feng, G., Du, P., Krett, N. L., Tessel, M. A., Rosen, S. T., Kibbe, W. A., & Lin, S. M. (2010) · BMC Research Notes · doi:10.1186/1756-0500-3-10 · Cited by 51 · see citing works
Self-citationGeMInA, Genomic Metadata for Infectious Agents, a geospatial surveillance pathogen database
Schriml, L. M., Arze, C., Nadendla, S., et al. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp832 · Cited by 31 · see citing works
Self-citationMining Biomedical Data Using MetaMap Transfer (MMTx) and the Unified Medical Language System (UMLS)
Osborne, J. D., Lin, S. M., Zhu, L. J., et al. (2007) · Methods in molecular biology · doi:10.1007/978-1-59745-547-3_9 · Cited by 30 · see citing works
Aymé, S., Rath, A., & Bellet, B. (2010) · Orphanet Journal of Rare Diseases · doi:10.1186/1750-1172-5-s1-p1 · Cited by 27 · see citing works
The Cell Line Ontology and its use in tagging cell line names in biomedical text.
Sarntivijai, S., Ade, A. S., Athey, B. D., & States, D. J. (2007) · PubMed · Cited by 6 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
The NHGRI GWAS Catalog, a curated resource of SNP-trait associations
Welter, D., MacArthur, J., Morales, J., Burdett, T., Hall, P., Junkins, H., Klemm, A., Flicek, P., Manolio, T., Hindorff, L., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1229 · Cited by 2,707 · see citing works
The Reactome pathway knowledgebase
Croft, D., Mundo, A. F., Haw, R., Milacic, M., Weiser, J., Wu, G., Caudy, M., Garapati, P., Gillespie, M., Kamdar, M. R., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1102 · Cited by 1,889 · see citing works
DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes
Pinero, J., Queralt-Rosinach, N., Bravo, A., Deu-Pons, J., Bauer-Mehren, A., Baron, M., Sanz, F., & Furlong, L. I. (2015) · Database · doi:10.1093/database/bav028 · Cited by 1,124 · see citing works
SIRT5-mediated lysine desuccinylation impacts diverse metabolic pathways
Park, J., Chen, Y., Tishkoff, D. X., Peng, C., Tan, M., Dai, L., Xie, Z., Zhang, Y., Zwaans, B. M. M., Skinner, M. E., et al. (2013) · Molecular Cell · doi:10.1016/j.molcel.2013.06.001 · Cited by 1,000 · see citing works
DISEASES: Text mining and data integration of disease–gene associations
Pletscher-Frankild, S., Pallejà, A., Tsafou, K., Binder, J. X., & Jensen, L. J. (2015) · Methods · doi:10.1016/j.ymeth.2014.11.020 · Cited by 591 · see citing works
TRRUST: a reference database of human transcriptional regulatory interactions
Han, H., Shim, H., Shin, D., Shim, J. E., Ko, Y., Shin, J., Kim, H., Cho, A., Kim, E., Lee, T., et al. (2015) · Scientific Reports · doi:10.1038/srep11432 · Cited by 462 · see citing works
Graph representation learning in biomedicine and healthcare
Li, M. M., Huang, K., & Zitnik, M. (2022) · Nature Biomedical Engineering · doi:10.1038/s41551-022-00942-x · Cited by 294 · see citing works
Pharos: collating protein information to shed light on the druggable genome
Nguyen, D.-T., Mathias, S., Bologa, C., Brunak, S., Fernandez, N., Gaulton, A., Hersey, A., Holmes, J., Jensen, L. J., Karlsson, A., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1072 · Cited by 279 · see citing works
CancerMine: a literature-mined resource for drivers, oncogenes and tumor suppressors in cancer
Lever, J., Zhao, E. Y., Grewal, J., Jones, M. R., & Jones, S. J. M. (2019) · Nature Methods · doi:10.1038/s41592-019-0422-y · Cited by 205 · see citing works
Himmelstein, D. S., & Baranzini, S. E. (2015) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004259 · Cited by 172 · see citing works
TCRD and pharos 2021: mining the human proteome for disease biology
Sheils, T. K., Mathias, S. L., Kelleher, K. J., Siramshetty, V. B., Nguyen, D.-T., Bologa, C. G., Jensen, L. J., Vidović, D., Koleti, A., Schürer, S. C., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa993 · Cited by 160 · see citing works
Pharos 2023: an integrated resource for the understudied human proteome
Kelleher, K. J., Sheils, T. K., Mathias, S. L., Yang, J. J., Metzger, V. T., Siramshetty, V. B., Nguyen, D.-T., Jensen, L. J., Vidović, D., Schürer, S. C., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkac1033 · Cited by 137 · see citing works
Towards precision medicine: advances in computational approaches for the analysis of human variants
Peterson, T. A., Doughty, E., & Kann, M. G. (2013) · Journal of Molecular Biology · doi:10.1016/j.jmb.2013.08.008 · Cited by 123 · see citing works
Co-design of human-centered, explainable AI for clinical decision support
Panigutti, C., Beretta, A., Fadda, D., Giannotti, F., Pedreschi, D., Perotti, A., & Rinzivillo, S. (2023) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3587271 · Cited by 127 · see citing works
Literome: PubMed-scale genomic knowledge base in the cloud
Poon, H., Quirk, C., DeZiel, C., & Heckerman, D. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu383 · Cited by 73 · see citing works
Nelson, C. A., Butte, A. J., & Baranzini, S. E. (2019) · Nature Communications · doi:10.1038/s41467-019-11069-0 · Cited by 85 · see citing works
Zhou, H., Cao, H., Matyunina, L., Shelby, M., Cassels, L., McDonald, J. F., & Skolnick, J. (2020) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.9b01248 · Cited by 39 · see citing works
Unveiling new disease, pathway, and gene associations via multi-scale neural network
Gaudelet, T., Malod-Dognin, N., Sánchez-Valle, J., Pancaldi, V., Valencia, A., & Pržulj, N. (2020) · PLoS ONE · doi:10.1371/journal.pone.0231059 · Cited by 25 · see citing works
The cell line ontology-based representation, integration and analysis of cell lines used in China
Pan, H., Bian, X., Yang, S., He, Y., Yang, X., & Liu, Y. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-2724-6 · Cited by 20 · see citing works
Dhrangadhariya, A., & Müller, H. (2023) · JAMIA Open · doi:10.1093/jamiaopen/ooac107 · Cited by 18 · see citing works
Yu, C., Zong, H., Chen, Y., Zhou, Y., Liu, X., Lin, Y., Li, J., Zheng, X., Min, H., & Shen, B. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae136 · Cited by 13 · see citing works
An Interoperable UMLS Terminology Service Using FHIR
Saripalle, R., Sookhak, M., & Haghparast, M. (2020) · Future Internet · doi:10.3390/fi12110199 · Cited by 8 · see citing works
- Authors
- Schriml, L. M., Arze, C., Nadendla, S., Chang, Y.-W. W., Mazaitis, M., Felix, V., Feng, G., & Kibbe, W. A.
- Affiliations
- Northwestern University (US)
- Corresponding author
- Schriml, L. M.
- Kibbe, W. A.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-11-12
- Volume
- 40
- Issue
- D1
- Pages
- D940-D946
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC3245088
- OpenAlex
- W2159092541
- Cited by
- 929
- References
- 28
- Citations by year
- 2026: 30 · 2025: 40 · 2024: 64 · 2023: 58 · 2022: 73 · 2021: 81 · 2020: 86 · 2019: 70 · 2018: 94 · 2017: 92 · 2016: 67 · 2015: 58 · 2014: 57 · 2013: 46 · 2012: 13
- FWCI
- 15.05
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nucleic Acids Research (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- National Institutes of Health
- National Center for Research Resources (R01RR025342, UL1RR025741)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Physical Sciences › Computer Science › Artificial Intelligence › Semantic Web and Ontologies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- disease ontology, graph databases, full-text search, mesh, ICD, SNOMED CT, OMIM, disease annotation, biomedical ontologies
- MeSH terms
- Computer Graphics, Disease, Humans, Terminology as Topic, Semantics, Software, User-Computer Interface, Databases, Factual, Vocabulary, Controlled
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
