A Census of Disease Ontologies
Abstract
For centuries, humans have sought to classify diseases based on phenotypic presentation and available treatments. Today, a wide landscape of strategies, resources, and tools exist to classify patients and diseases. Ontologies can provide a robust foundation of logic for precise stratification and classification along diverse axes such as etiology, development, treatment, and genetics. Disease and phenotype ontologies are used in four primary ways: ( a) search, retrieval, and annotation of knowledge; ( b) data integration and analysis; ( c) clinical decision support; and ( d) knowledge discovery. Computational inference can connect existing knowledge and generate new insights and hypotheses about drug targets, prognosis prediction, or diagnosis. In this review, we examine the rise of disease and phenotype ontologies and the diverse ways they are represented and applied in biomedicine.
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The Monarch Disease Ontology (Mondo) is emerging as a comprehensive, community-driven, and computationally-driven resource.
“While numerous disease and phenotype ontologies exist (44), the Monarch Disease Ontology (Mondo) is emerging as a comprehensive, community-driven, and computationally-driven resource (45).”
From Artificial Intelligence for Drug Discovery: Are We There Yet? (2024) · cites this paper as [45]
Cites
Diagnostic and Statistical Manual of Mental Disorders
American Psychiatric Association (2013) · doi:10.1176/appi.books.9780890425596 · Cited by 116,369 · see citing works
A translation approach to portable ontology specifications
Gruber, T. (1993) · Knowledge Acquisition · doi:10.1006/knac.1993.1008 · Cited by 13,568 · see citing works
GREAT improves functional interpretation of cis-regulatory regions
McLean, C. Y., Bristor, D., Hiller, M., Clarke, S. L., Schaar, B. T., Lowe, C. B., Wenger, A. M., & Bejerano, G. (2010) · Nature Biotechnology · doi:10.1038/nbt.1630 · Cited by 4,502 · see citing works
Amberger, J. S., Bocchini, C. A., Schiettecatte, F., Scott, A. F., & Hamosh, A. (2015) · Nucleic Acids Research · doi:10.1093/nar/gku1205 · Cited by 2,691 · see citing works
The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration
Smith, B., Ashburner, M., Rosse, C., Bard, J., Bug, W. J., Ceusters, W. M., Goldberg, L. J., Eilbeck, K. L., Ireland, A., Mungall, C., et al. (2007) · Nature Biotechnology · doi:10.1038/nbt1346 · Cited by 2,546 · see citing works
Self-citationDOSE: an R/Bioconductor package for disease ontology semantic and enrichment analysis
Yu, G., Wang, L.-G., Yan, G., & He, Q. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu684 · Cited by 1,280 · see citing works
Understanding multicellular function and disease with human tissue-specific networks
Greene, C. S., Krishnan, A., Wong, A. K., Ricciotti, E., Zelaya, R. A., Himmelstein, D. S., Zhang, R., Hartmann, B. M., Zaslavsky, E., Sealfon, S. C., et al. (2015) · Nature Genetics · doi:10.1038/ng.3259 · Cited by 832 · see citing works
Resolution of Disease Phenotypes Resulting from Multilocus Genomic Variation
Posey, J. E., Harel, T., Liu, P., Rosenfeld, J. A., James, R. A., Coban‐Akdemir, Z., Walkiewicz, M. A., Bi, W., Xiao, R., Ding, Y., et al. (2016) · New England Journal of Medicine · doi:10.1056/nejmoa1516767 · Cited by 772 · see citing works
The Human Phenotype Ontology in 2017
Köhler, S., Vasilevsky, N., Engelstad, M., Foster, E. D., McMurry, J. A., Aymé, S., Baynam, G. S., Bello, S. M., Boerkoel, C. F., Boycott, K. M., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw1039 · Cited by 757 · see citing works
Self-citationPersonalized Immunomonitoring Uncovers Molecular Networks that Stratify Lupus Patients
Banchereau, R., Hong, S., Cantarel, B. L., Baldwin, N. E., Baisch, J. M., Edens, M., Cepika, A., Acs, P., Turner, J., Anguiano, E., et al. (2016) · Cell · doi:10.1016/j.cell.2016.03.008 · Cited by 735 · see citing works
Uberon, an integrative multi-species anatomy ontology
Mungall, C. J., Torniai, C., Gkoutos, G. V., Lewis, S. E., & Haendel, M. A. (2012) · Genome biology · doi:10.1186/gb-2012-13-1-r5 · Cited by 732 · cited 1× · see citing works
“This release is a direct transformation of the NCIt using OBO-style term Internationalized Resource Identifiers and annotation properties, with direct references to terms from other domain-specific OBO Library ontologies [e.g., Cell Type Ontology (60) and the Uberon Anatomy Ontology (61)].”
MethodGriffith, M., Spies, N. C., Krysiak, K., McMichael, J. F., Coffman, A. C., Danos, A. M., Ainscough, B. J., Ramirez, C. A., Rieke, D. T., Kujan, L., et al. (2017) · Nature Genetics · doi:10.1038/ng.3774 · Cited by 628 · see citing works
Clinical Diagnostics in Human Genetics with Semantic Similarity Searches in Ontologies
Köhler, S., Schulz, M. H., Krawitz, P., Bauer, S., Dölken, S., Ott, C. E., Mundlos, C., Horn, D., Mundlos, S., & Robinson, P. N. (2009) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2009.09.003 · Cited by 590 · see citing works
Self-citationKibbe, W. A., Arze, C., Felix, V., Mitraka, E., Bolton, E., Fu, G., Mungall, C., Binder, J. X., MALONE, J. M., Vasant, D., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1011 · Cited by 582 · see citing works
Self-citationModeling sample variables with an Experimental Factor Ontology
Malone, J., Holloway, E., Adamusiak, T., Kapushesky, M., Zheng, J., Kolesnikov, N. N., Zhukova, A., Brāzma, A., & Parkinson, H. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq099 · Cited by 571 · see citing works
Deep phenotyping for precision medicine
Robinson, P. N. (2012) · Human Mutation · doi:10.1002/humu.22080 · Cited by 471 · see citing works
Self-citationThe Matchmaker Exchange: A Platform for Rare Disease Gene Discovery
Philippakis, A., Azzariti, D. R., Beltrán, S., Brookes, A. J., Brownstein, C. A., Brudno, M., Brunner, H. G., Buske, O. J., Carey, K., Doll, C., et al. (2015) · Human Mutation · doi:10.1002/humu.22858 · Cited by 470 · see citing works
Self-citationNext-generation diagnostics and disease-gene discovery with the Exomiser
Smedley, D., Jacobsen, J. O. B., Jäger, M., Köhler, S., Holtgrewe, M., Schubach, M., Siragusa, E., Zemojtel, T., Buske, O. J., Washington, N. L., et al. (2015) · Nature Protocols · doi:10.1038/nprot.2015.124 · Cited by 445 · see citing works
Self-citationMungall, C. J., McMurry, J. A., Köhler, S., Balhoff, J. P., Borromeo, C., Brush, M., Carbon, S., Conlin, T., Dunn, N., Engelstad, M., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1128 · Cited by 441 · see citing works
Self-citationNewton, K. M., Peissig, P. L., Kho, A. N., Bielinski, S. J., Berg, R. L., Choudhary, V., Basford, M., Chute, C. G., Kullo, I. J., Li, R., et al. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2012-000896 · Cited by 414 · see citing works
Self-citationNatural and political observations made upon the bills of mortality
Graunt, J., & Willcox, W. F. (1939) · Medical Entomology and Zoology · Cited by 402 · see citing works
Wei, W., Bastarache, L. A., Carroll, R. J., Marlo, J. E., Osterman, T. J., Gamazon, E. R., Cox, N. J., Roden, D. M., & Denny, J. C. (2017) · PLoS ONE · doi:10.1371/journal.pone.0175508 · Cited by 380 · see citing works
The Cell Ontology 2016: enhanced content, modularization, and ontology interoperability
Diehl, A. D., Meehan, T. F., Bradford, Y. M., Brush, M., Dahdul, W., Dougall, D. S., He, Y. O., Osumi-Sutherland, D., Ruttenberg, A., Sarntivijai, S., et al. (2016) · Journal of Biomedical Semantics · doi:10.1186/s13326-016-0088-7 · Cited by 332 · see citing works
Self-citationThe NCI Genomic Data Commons as an engine for precision medicine
Jensen, M. A., Ferretti, V., Grossman, R. L., & Staudt, L. M. (2017) · Blood · doi:10.1182/blood-2017-03-735654 · Cited by 317 · 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
Self-citationForrey, A. W., McDonald, C. J., DeMoor, G., Huff, S. M., Leavelle, D., Leland, D., Fiers, T., Charles, L., Griffin, B., Stalling, F., et al. (1996) · Clinical Chemistry · doi:10.1093/clinchem/42.1.81 · Cited by 277 · see citing works
Żemojtel, T., Köhler, S., Mackenroth, L., Jäger, M., Hecht, J., Krawitz, P. M., Graul-Neumann, L. M., Doelken, S. C., Ehmke, N., Spielmann, M., et al. (2014) · Science Translational Medicine · doi:10.1126/scitranslmed.3009262 · Cited by 252 · see citing works
Self-citationBragin, E., Chatzimichali, E. A., Wright, C. F., Hurles, M. E., Firth, H. V., Bevan, A. P., & Swaminathan, G. J. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt937 · Cited by 233 · see citing works
Ryerson, C. J., Corte, T. J., Lee, J., et al. (2017) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201702-0400pp · Cited by 226 · see citing works
The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease
Groza, T., Köhler, S., Moldenhauer, D., Vasilevsky, N., Baynam, G. S., Żemojtel, T., Schriml, L. M., Kibbe, W. A., Schofield, P. N., Beck, T., et al. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.05.020 · Cited by 224 · see citing works
Self-citationAdvances in Electronic Phenotyping: From Rule-Based Definitions to Machine Learning Models
Banda, J. M., Seneviratne, M. G., Hernandez‐Boussard, T., & Shah, N. H. (2018) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-080917-013315 · Cited by 223 · see citing works
An upper‐level ontology for the biomedical domain
McCray, A. T. (2003) · Comparative and Functional Genomics · doi:10.1002/cfg.255 · Cited by 216 · see citing works
Clinical Practice Guidelines for Rare Diseases: The Orphanet Database
Pavan, S., Rommel, K., Marquina, M. E. M., Höhn, S., Serrière-Lanneau, V., & Rath, A. (2017) · PLoS ONE · doi:10.1371/journal.pone.0170365 · Cited by 191 · see citing works
Singleton, M., Guthery, S. L., Voelkerding, K. V., Chen, K., Kennedy, B., Margraf, R. L., Durtschi, J., Eilbeck, K. L., Reese, M. G., Jorde, L. B., et al. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.03.010 · Cited by 186 · see citing works
Toward a Medical-concept Representation Language
Evans, D. A., Cimino, J. J., Hersh, W., et al. (1994) · Journal of the American Medical Informatics Association · doi:10.1136/jamia.1994.95236153 · Cited by 150 · see citing works
Deletions of chromosomal regulatory boundaries are associated with congenital disease
Ibn-Salem, J., Köhler, S., Love, M. I., Chung, H.-R., Huang, N., Hurles, M. E., Haendel, M., Washington, N. L., Smedley, D., Mungall, C. J., et al. (2014) · Genome Biology · doi:10.1186/s13059-014-0423-1 · Cited by 143 · see citing works
Self-citationPhenoDigm: analyzing curated annotations to associate animal models with human diseases
Smedley, D. P., Oellrich, A., Köhler, S., et al. (2013) · Database · doi:10.1093/database/bat025 · Cited by 137 · see citing works
A Terminological and Ontological Analysis of the NCI Thesaurus
Smith, B., Goldberg, L. J., & Ceusters, W. M. (2005) · Methods of Information in Medicine · doi:10.1055/s-0038-1634000 · Cited by 126 · see citing works
Cowell, L. G., & Smith, B. (2009) · Springer eBooks · doi:10.1007/978-1-4419-1327-2_19 · Cited by 124 · see citing works
Bone, W. P., Washington, N. L., Buske, O. J., Adams, D. R., Davis, J., Draper, D. D., Flynn, E. D., Gîrdea, M., Godfrey, R. A., Golas, G. A., et al. (2015) · Genetics in Medicine · doi:10.1038/gim.2015.137 · Cited by 103 · see citing works
Self-citationFormal Ontology in Information Systems
Aussenac-Gilles, N., Galton, A., Hahmann, T., et al. (2021) · Frontiers in artificial intelligence and applications · doi:10.3233/faia344 · Cited by 94 · see citing works
MeSH Now: Automatic MeSH indexing at PubMed scale via learning to rank
Mao, Y., & Lu, Z. (2017) · Journal of Biomedical Semantics · doi:10.1186/s13326-017-0123-3 · Cited by 87 · see citing works
Köhler, S., Doelken, S. C., Ruef, B. J., Bauer, S., Washington, N. L., Westerfield, M., Gkoutos, G. V., Schofield, P. N., Smedley, D. P., Lewis, S., et al. (2013) · F1000Research · doi:10.12688/f1000research.2-30.v2 · Cited by 83 · see citing works
Self-citationFoundations 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
Introduction to Bio-Ontologies
Robinson, P. N., & Bauer, S. (2011) · Chapman & Hall/CRC eBooks · doi:10.1201/b10967 · Cited by 73 · see citing works
Self-citationIntegrating personalized gene expression profiles into predictive disease-associated gene pools
Menche, J., Güney, E., Sharma, A., Branigan, P. J., Loza, M. J., Baribaud, F., Dobrin, R., & Barabási, A.-Ĺ. (2017) · npj Systems Biology and Applications · doi:10.1038/s41540-017-0009-0 · Cited by 70 · see citing works
Porter, J. F., Kingsland Lawrence, C., Lindberg, D. A. B., et al. (1988) · Arthritis & Rheumatism · doi:10.1002/art.1780310210 · Cited by 69 · see citing works
Bayesian ontology querying for accurate and noise-tolerant semantic searches
Bauer, S., Köhler, S., Schulz, M. H., & Robinson, P. N. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts471 · Cited by 66 · see citing works
Self-citationJoseph, S., Barai, R. S., Rasika, B., & Idicula‐Thomas, S. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1146 · Cited by 59 · see citing works
An ontology-driven, case-based clinical decision support model for removable partial denture design
Chen, Q., Wu, J. Y., Li, S., et al. (2016) · Scientific Reports · doi:10.1038/srep27855 · Cited by 59 · see citing works
Zhang, Y., Gou, L., Zhou, T., Lin, D., Zheng, J., Li, Y., & Li, J. (2017) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2017.06.021 · Cited by 57 · see citing works
Sharing Clinical and Genomic Data on Cancer — The Need for Global Solutions
The Clinical Cancer Genome Task Team of the Global Alliance for Genomics and Health (2017) · New England Journal of Medicine · doi:10.1056/nejmp1612254 · Cited by 53 · see citing works
Enabling enrichment analysis with the Human Disease Ontology
LePendu, P., Musen, M. A., & Shah, N. H. (2011) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2011.04.007 · Cited by 49 · see citing works
Boyce, R. D., Ryan, P. B., Norén, G. N., Schuemie, M. J., Reich, C., Duke, J. D., Tatonetti, N. P., Trifirò, G., Harpaz, R., Overhage, J. M., et al. (2014) · Drug Safety · doi:10.1007/s40264-014-0189-0 · Cited by 49 · see citing works
Recent advances in predicting gene–disease associations
Opap, K., & Mulder, N. (2017) · F1000Research · doi:10.12688/f1000research.10788.1 · Cited by 49 · see citing works
Scalable quality assurance for large SNOMED CT hierarchies using subject-based subtaxonomies
Ochs, C., Geller, J., Perl, Y., et al. (2014) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2014-003151 · Cited by 48 · see citing works
Defining Phenotypes from Clinical Data to Drive Genomic Research
Robinson, J. R., Wei, W., Roden, D. M., & Denny, J. C. (2018) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-080917-013335 · Cited by 48 · see citing works
The neurological disease ontology
Jensen, M., Cox, A. P., Chaudhry, N., et al. (2013) · Journal of Biomedical Semantics · doi:10.1186/2041-1480-4-42 · Cited by 46 · see citing works
Modeling the Autism Spectrum Disorder Phenotype
McCray, A. T., Trevvett, P., & Frost, H. R. (2013) · Neuroinformatics · doi:10.1007/s12021-013-9211-4 · Cited by 45 · see citing works
THE INTERNATIONAL CLASSIFICATION OF DISEASE AND CAUSES OF DEATH AND ITS REVISION
(1929) · The Medical Journal of Australia · doi:10.5694/j.1326-5377.1929.tb13889.x · Cited by 45 · see citing works
RAPID: Resource of Asian Primary Immunodeficiency Diseases
Keerthikumar, S., Raju, R., Kandasamy, K., et al. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn682 · Cited by 43 · see citing works
There Are Important Reasons For Delaying Implementation Of The New ICD-10 Coding System
Chute, C. G., Huff, S. M., Ferguson, J. A., Walker, J. M., & Halamka, J. D. (2012) · Health Affairs · doi:10.1377/hlthaff.2011.1258 · Cited by 42 · see citing works
Self-citationAdaptation of machine translation for multilingual information retrieval in the medical domain
Pecina, P., Dušek, O., Goeuriot, L., Hajič, J., Hlaváčová, J., Jones, G. J. F., Kelly, L., Leveling, J., Mareček, D., Novák, M., et al. (2014) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2014.01.004 · Cited by 41 · see citing works
Younesi, E., Malhotra, A., Gündel, M., et al. (2015) · Theoretical Biology and Medical Modelling · doi:10.1186/s12976-015-0017-y · Cited by 40 · see citing works
Brucellosis Ontology (IDOBRU) as an extension of the Infectious Disease Ontology
Lin, Y., Xiang, Z., & He, Y. O. (2011) · Journal of Biomedical Semantics · doi:10.1186/2041-1480-2-9 · Cited by 40 · see citing works
Maritz, R., Aronsky, D., & Prodinger, B. (2017) · Applied Clinical Informatics · doi:10.4338/aci-2017050078 · Cited by 39 · see citing works
Sarntivijai, S., Vasant, D., Jupp, S., et al. (2016) · Journal of Biomedical Semantics · doi:10.1186/s13326-016-0051-7 · Cited by 38 · see citing works
Systematized Nomenclature of Pathology.
(1965) · Annals of Internal Medicine · doi:10.7326/0003-4819-63-6-1172_1 · Cited by 38 · see citing works
Abidi, S. (2017) · Journal of Medical Systems · doi:10.1007/s10916-017-0841-1 · Cited by 35 · see citing works
Standard Nomenclature of Diseases and Operations.
(1961) · Annals of Internal Medicine · doi:10.7326/0003-4819-55-5-878_2 · Cited by 34 · see citing works
Scalable representations of diseases in biomedical ontologies
Schulz, S., Spackman, K. A., James, A. G., et al. (2011) · Journal of Biomedical Semantics · doi:10.1186/2041-1480-2-s2-s6 · Cited by 33 · see citing works
Maurice, P., Dhombres, F., Blondiaux, E., Friszer, S., Guilbaud, L., Lelong, N., Khoshnood, B., Charlet, J., Perrot, N., Jauniaux, E., et al. (2017) · Journal of Gynecology Obstetrics and Human Reproduction · doi:10.1016/j.jogoh.2017.03.004 · Cited by 33 · see citing works
Standard Nomenclature of Diseases and Operations
THOMPSON, E. T., & Hayden, A. C. (1952) · JAMA · doi:10.1001/jama.1952.02930200097034 · Cited by 29 · see citing works
The Disease Portals, disease-gene annotation and the RGD disease ontology at the Rat Genome Database
Hayman, G. T., Laulederkind, S. J. F., Smith, J. R., Wang, S.-J., Petri, V., Nigam, R., Tutaj, M., De Pons, J., Dwinell, M. R., & Shimoyama, M. (2016) · Database · doi:10.1093/database/baw034 · Cited by 27 · see citing works
Towards Annotating Potential Incoherences in BioPortal Mappings
Faria, D., Jiménez-Ruiz, E., Pesquita, C., et al. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-11915-1_2 · Cited by 25 · see citing works
Jiang, G., Solbrig, H. R., & Chute, C. G. (2012) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2011-000739 · Cited by 24 · see citing works
Self-citationMugzach, O., Mor Peleg, B., Bagley, S. C., Guter, S. J., Cook, E. H., & Altman, R. B. (2015) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2015.06.026 · Cited by 23 · see citing works
Systematized nomenclature of human and veterinary medicine : SNOMED international
Côté, R. A. (1993) · Medical Entomology and Zoology · Cited by 21 · see citing works
Mungall, C., Koehler, S., Robinson, P. N., Holmes, I. H., & Haendel, M. A. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/048843 · Cited by 20 · see citing works
Self-citationAnnotating the Function of the Human Genome with Gene Ontology and Disease Ontology
Hu, Y., Zhou, W., Ren, J., et al. (2016) · BioMed Research International · doi:10.1155/2016/4130861 · Cited by 20 · see citing works
Wang, L., Li, M., Xie, J., Cao, Y., Liu, H., & He, Y. O. (2017) · Scientific Reports · doi:10.1038/s41598-017-12580-4 · Cited by 20 · see citing works
Fu, X., Batista-Navarro, R., Rak, R., & Ananiadou, S. (2015) · Journal of Biomedical Semantics · doi:10.1186/s13326-015-0004-6 · Cited by 19 · see citing works
Mulder, N., Nembaware, V., Adekile, A. D., et al. (2016) · Applied & Translational Genomics · doi:10.1016/j.atg.2016.03.005 · Cited by 19 · see citing works
Jouhet, V., Mougin, F., Brechat, B., et al. (2017) · Journal of Biomedical Semantics · doi:10.1186/s13326-017-0114-4 · Cited by 18 · see citing works
Eighteenth Century Classification of Mental Illness
Munsche, H. A., & Whitaker, H. A. (2012) · Cognitive and Behavioral Neurology · doi:10.1097/wnn.0b013e31827de594 · Cited by 17 · see citing works
DermO; an ontology for the description of dermatologic disease
Fisher, H. M., Hoehndorf, R., Bazelato, B. S., et al. (2016) · Journal of Biomedical Semantics · doi:10.1186/s13326-016-0085-x · Cited by 17 · see citing works
Strathdee, S. A., & Beyrer, C. (2015) · New England Journal of Medicine · doi:10.1056/nejmc1510396 · Cited by 16 · see citing works
Clare, A. J., Wicky, H. E., Empson, R. M., & Hughes, S. M. (2017) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2017.00283 · Cited by 16 · see citing works
Min, H., Mobahi, H., Irvin, K., Avramovic, S., & Wojtusiak, J. (2017) · Journal of Biomedical Semantics · doi:10.1186/s13326-017-0149-6 · Cited by 16 · see citing works
Mitchell, J. A., Loughman, W. D., & Epstein, C. J. (1980) · American Journal of Medical Genetics · doi:10.1002/ajmg.1320070304 · Cited by 12 · see citing works
Chen, W., Kowatch, R. A., Lin, S., Splaingard, M., & Huang, Y. (2015) · Applied Clinical Informatics · doi:10.4338/aci-2014-11-ra-0106 · Cited by 12 · see citing works
A Semantic-Based Model for Triage Patients in Emergency Departments
Wunsch, G., da Costa, C. A., & Righi, R. D. R. (2017) · Journal of Medical Systems · doi:10.1007/s10916-017-0710-y · Cited by 12 · see citing works
Relating Complexity and Error Rates of Ontology Concepts
Zheng, L., Perl, Y., Halper, M. H., et al. (2017) · Methods of Information in Medicine · doi:10.3414/me16-01-0085 · Cited by 11 · see citing works
Elhanan, G., Ochs, C., Mejino, J. L. V., Liu, H., Mungall, C., & Perl, Y. (2017) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2017.05.002 · Cited by 11 · see citing works
Self-citationComparative analysis of weighted gene co-expression networks in human and mouse
Eidsaa, M., Stubbs, L. J., & Almaas, E. (2017) · PLoS ONE · doi:10.1371/journal.pone.0187611 · Cited by 11 · see citing works
Improving information retrieval in functional analysis
Rodríguez, J. C., González, G. A., Fresno, C., Llera, A. S., & Fernández, E. A. (2016) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2016.09.017 · Cited by 8 · see citing works
Mizuno, S., Ogishima, S., Nishigori, H., Jamieson, D. G., Verspoor, K. M., Tanaka, H., Yaegashi, N., & Nakaya, J. (2016) · PLoS ONE · doi:10.1371/journal.pone.0162828 · Cited by 8 · see citing works
An ontology-based consultation system to support medical care on board seagoing vessels
Carletti, G., Giuliodori, P., Pietri, V. D., et al. (2016) · International Maritime Health · doi:10.5603/imh.2016.0004 · Cited by 7 · see citing works
The ‘Preliminary Discourse’ to Methodical Nosology , by François Boissier de Sauvages (1772)
Starkstein, S., & Berrios, G. E. (2015) · History of Psychiatry · doi:10.1177/0957154x15602361 · Cited by 7 · see citing works
Towards an Expert System for Accurate Diagnosis and Progress Monitoring of Parkinson’s Disease
Alexiou, A. T., Psiha, M., & Vlamos, P. (2014) · Advances in experimental medicine and biology · doi:10.1007/978-3-319-08927-0_17 · Cited by 5 · see citing works
An extensible framework and database of infectious disease for biosurveillance
Daughton, A. R., Priedhorsky, R., Fairchild, G., et al. (2017) · BMC Infectious Diseases · doi:10.1186/s12879-017-2650-z · Cited by 3 · see citing works
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How many rare diseases are there?
Haendel, M., Vasilevsky, N., Unni, D., Bologa, C., Harris, N., Rehm, H., Hamosh, A., Baynam, G., Groza, T., McMurry, J., et al. (2020) · Nature Reviews Drug Discovery · doi:10.1038/d41573-019-00180-y · Cited by 554 · see citing works
Self-citationMungall, C. J., McMurry, J. A., Köhler, S., Balhoff, J. P., Borromeo, C., Brush, M., Carbon, S., Conlin, T., Dunn, N., Engelstad, M., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1128 · Cited by 441 · see citing works
Self-citationArtificial Intelligence for Drug Discovery: Are We There Yet?
Hasselgren, C., & Oprea, T. I. (2024) · Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-040323-040828 · Cited by 236 · see citing works
Mondo: Unifying diseases for the world, by the world
Vasilevsky, N. A., Matentzoglu, N. A., Toro, S., Flack, J. E., Hegde, H., Unni, D. R., Alyea, G. F., Amberger, J. S., Babb, L., Balhoff, J. P., et al. (2022) · doi:10.1101/2022.04.13.22273750 · Cited by 107 · see citing works
Self-citation
- Authors
- Haendel, M. A., McMurry, J. A., Relevo, R., Mungall, C. J., Robinson, P. N., & Chute, C. G.
- Affiliations
- Oregon State University (US)
- Oregon Health & Science University (US)
- Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
- Jackson Laboratory (US)
- Johns Hopkins University (US)
- Venue
- Annual Review of Biomedical Data Science
- Publisher
- Annual Reviews
- Published
- 2018-07-20
- Volume
- 1
- Issue
- 1
- Pages
- 305-331
- ISSN
- 2574-3414 (ISSN-L)
- OpenAlex
- W2802673730
- Cited by
- 49
- References
- 101
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 7 · 2023: 6 · 2022: 5 · 2021: 8 · 2020: 7 · 2019: 7 · 2018: 2 · 2016: 1
- FWCI
- 0.59
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Annual Review of Biomedical Data Science (publishedVersion)
- Funders
- Eli Lilly and Company
- National Institutes of Health
- 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, phenotype ontologies, disease classification, knowledge representation, clinical decision support, data integration, knowledge discovery, computational inference, drug target identification, outcome prediction, diagnosis
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 ›
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