| Title: |
The Human Phenotype Ontology in 2024: phenotypes around the world |
| Authors: |
Gargano, MA; Matentzoglu, N; Coleman, B; Addo-Lartey, EB; Anagnostopoulos, AV; Anderton, J; Avillach, P; Bagley, AM; Bakštein, E; Balhoff, JP; Baynam, G; Bello, SM; Berk, M; Bertram, H; Bishop, S; Blau, H; Bodenstein, DF; Botas, P; Boztug, K; Čady, J; Callahan, TJ; Cameron, R; Carbon, SJ; Castellanos, F; Caufield, JH; Chan, LE; Chute, CG; Cruz-Rojo, J; Dahan-Oliel, N; Davids, JR; Dieuleveult, M; Souza, V; de Vries, BBA; Vries, E; DePaulo, JR; Derfalvi, B; Dhombres, F; Diaz-Byrd, C; Dingemans, AJM; Donadille, B; Duyzend, M; Elfeky, R; Essaid, S; Fabrizzi, C; Fico, G; Firth, HV; Freudenberg-Hua, Y; Fullerton, JM; Gabriel, DL; Gilmour, K; Giordano, J; Goes, FS; Moses, RG; Green, I; Griese, M; Groza, T; Gu, W; Guthrie, J; Gyori, B; Hamosh, A; Hanauer, M; Hanušová, K; He, Y; Hegde, H; Helbig, I; Holasová, K; Hoyt, CT; Huang, S; Hurwitz, E; Jacobsen, JOB; Jiang, X; Joseph, L; Keramatian, K; King, B; Knoflach, K; Koolen, DA; Kraus, ML; Kroll, C; Kusters, M; Ladewig, MS; Lagorce, D; Lai, MC; Lapunzina, P; Laraway, B; Lewis-Smith, D; Li, X; Lucano, C; Majd, M; Marazita, ML; Martinez-Glez, V; McHenry, TH; McInnis, MG; McMurry, JA; Mihulová, M; Millett, CE; Mitchell, PB; Moslerová, V; Narutomi, K; Nematollahi, S; Nevado, J |
| Source: |
urn:ISSN:0305-1048 ; urn:ISSN:1362-4962 ; Nucleic Acids Research, 52, D1, D1333-D1346 |
| Publisher Information: |
Oxford University Press (OUP) |
| Publication Year: |
2024 |
| Collection: |
UNSW Sydney (The University of New South Wales): UNSWorks |
| Subject Terms: |
31 Biological Sciences; 3105 Genetics; Networking and Information Technology R&D (NITRD); Machine Learning and Artificial Intelligence; Human Genome; Genetics; 4.1 Discovery and preclinical testing of markers and technologies; Generic health relevance; Humans; Biological Ontologies; Phenotype; Genomics; Algorithms; Rare Diseases; anzsrc-for: 31 Biological Sciences; anzsrc-for: 3105 Genetics; anzsrc-for: 05 Environmental Sciences; anzsrc-for: 06 Biological Sciences; anzsrc-for: 08 Information and Computing Sciences; anzsrc-for: 34 Chemical sciences; anzsrc-for: 41 Environmental sciences |
| Description: |
The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs. |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
unknown |
| Relation: |
https://hdl.handle.net/1959.4/103891; https://doi.org/10.1093/nar/gkad1005 |
| DOI: |
10.1093/nar/gkad1005 |
| Availability: |
https://hdl.handle.net/1959.4/103891; https://unsworks.unsw.edu.au/bitstreams/addc9a4d-7ea5-4a56-beeb-e01ce2d3d6a5/download; https://doi.org/10.1093/nar/gkad1005 |
| Rights: |
open access ; https://purl.org/coar/access_right/c_abf2 ; CC BY ; https://creativecommons.org/licenses/by/4.0/ ; free_to_read |
| Accession Number: |
edsbas.3850352A |
| Database: |
BASE |