The Human Phenotype Ontology in 2024: phenotypes around the world: phenotypes around the world

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Název: The Human Phenotype Ontology in 2024: phenotypes around the world: phenotypes around the world
Autoři: Michael A Gargano, Nicolas Matentzoglu, Ben Coleman, Eunice B Addo-Lartey, Anna V Anagnostopoulos, Joel Anderton, Paul Avillach, Anita M Bagley, Eduard Bakštein, James P Balhoff, Gareth Baynam, Susan M Bello, Michael Berk, Holli Bertram, Somer Bishop, Hannah Blau, David F Bodenstein, Pablo Botas, Kaan Boztug, Jolana Čady, Tiffany J Callahan, Rhiannon Cameron, Seth J Carbon, Francisco Castellanos, J Harry Caufield, Lauren E Chan, Christopher G Chute, Jaime Cruz-Rojo, Noémi Dahan-Oliel, Jon R Davids, Maud de Dieuleveult, Vinicius de Souza, Bert B A de Vries, Esther de Vries, J Raymond DePaulo, Beata Derfalvi, Ferdinand Dhombres, Claudia Diaz-Byrd, Alexander J M Dingemans, Bruno Donadille, Michael Duyzend, Reem Elfeky, Shahim Essaid, Carolina Fabrizzi, Giovanna Fico, Helen V Firth, Yun Freudenberg-Hua, Janice M Fullerton, Davera L Gabriel, Kimberly Gilmour, Jessica Giordano, Fernando S Goes, Rachel Gore Moses, Ian Green, Matthias Griese, Tudor Groza, Weihong Gu, Julia Guthrie, Benjamin Gyori, Ada Hamosh, Marc Hanauer, Kateřina Hanušová, Yongqun (Oliver) He, Harshad Hegde, Ingo Helbig, Kateřina Holasová, Charles Tapley Hoyt, Shangzhi Huang, Eric Hurwitz, Julius O B Jacobsen, Xiaofeng Jiang, Lisa Joseph, Kamyar Keramatian, Bryan King, Katrin Knoflach, David A Koolen, Megan L Kraus, Carlo Kroll, Maaike Kusters, Markus S Ladewig, David Lagorce, Meng-Chuan Lai, Pablo Lapunzina, Bryan Laraway, David Lewis-Smith, Xiarong Li, Caterina Lucano, Marzieh Majd, Mary L Marazita, Victor Martinez-Glez, Toby H McHenry, Melvin G McInnis, Julie A McMurry, Michaela Mihulová, Caitlin E Millett, Philip B Mitchell, Veronika Moslerová, Kenji Narutomi, Shahrzad Nematollahi, Julian Nevado, Andrew A Nierenberg, Nikola Novák Čajbiková, John I Nurnberger, Soichi Ogishima, Daniel Olson, Abigail Ortiz, Harry Pachajoa, Guiomar Perez de Nanclares, Amy Peters, Tim Putman, Christina K Rapp, Ana Rath, Justin Reese, Lauren Rekerle, Angharad M Roberts, Suzy Roy, Stephan J Sanders, Catharina Schuetz, Eva C Schulte, Thomas G Schulze, Martin Schwarz, Katie Scott, Dominik Seelow, Berthold Seitz, Yiping Shen, Morgan N Similuk, Eric S Simon, Balwinder Singh, Damian Smedley, Cynthia L Smith, Jake T Smolinsky, Sarah Sperry, Elizabeth Stafford, Ray Stefancsik, Robin Steinhaus, Rebecca Strawbridge, Jagadish Chandrabose Sundaramurthi, Polina Talapova, Jair A Tenorio Castano, Pavel Tesner, Rhys H Thomas, Audrey Thurm, Marek Turnovec, Marielle E van Gijn, Nicole A Vasilevsky, Markéta Vlčková, Anita Walden, Kai Wang, Ron Wapner, James S Ware, Addo A Wiafe, Samuel A Wiafe, Lisa D Wiggins, Andrew E Williams, Chen Wu, Margot J Wyrwoll, Hui Xiong, Nefize Yalin, Yasunori Yamamoto, Lakshmi N Yatham, Anastasia K Yocum, Allan H Young, Zafer Yüksel, Peter P Zandi, Andreas Zankl, Ignacio Zarante, Miroslav Zvolský, Sabrina Toro, Leigh C Carmody, Nomi L Harris, Monica C Munoz-Torres, Daniel Danis, Christopher J Mungall, Sebastian Köhler, Melissa A Haendel, Peter N Robinson
Přispěvatelé: DSpace at Cambridge pro (8.1), Psychiatry, School of Medicine
Zdroj: Nucleic Acids Res
D1346
D1333
Nucleic Acids Research, 52, D1, pp. D1333-d1346
Nucleic Acids Research, vol 52, iss D1
Nucleic Acids Research
Informace o vydavateli: Oxford University Press (OUP), 2023.
Rok vydání: 2023
Témata: Human Genetics - Radboud University Medical Center - DCMN, 3105 Genetics, Rare Diseases, anzsrc-for: 34 Chemical sciences, Information and Computing Sciences, Genetics, Machine Learning and Artificial Intelligence, Database Issue, Humans, anzsrc-for: 31 Biological Sciences, JMG, JGM, Human Genome, anzsrc-for: 05 Environmental Sciences, 3 Good Health and Well Being, Genomics, Biological Sciences, 3. Good health, Rare diseases, 4.1 Discovery and preclinical testing of markers and technologies, anzsrc-for: 41 Environmental sciences, Environmental sciences, anzsrc-for: 3105 Genetics, Biological sciences, Good Health and Well Being, Phenotype, Networking and Information Technology R&D (NITRD), Chemical sciences, Biological Ontologies, anzsrc-for: 06 Biological Sciences, Generic health relevance, anzsrc-for: 08 Information and Computing Sciences, Biological ontologies, Environmental Sciences, Algorithms, 31 Biological Sciences, Developmental Biology
Popis: 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.
Druh dokumentu: Article
Other literature type
Popis souboru: text/xml; application/zip; application/pdf
Jazyk: English
ISSN: 1362-4962
0305-1048
DOI: 10.1093/nar/gkad1005
Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/37953324
http://hdl.handle.net/10044/1/108678
https://repository.ubn.ru.nl/handle/2066/305172
https://repository.ubn.ru.nl//bitstream/handle/2066/305172/305172.pdf
https://www.repository.cam.ac.uk/handle/1810/379587
https://doi.org/10.1093/nar/gkad1005
https://www.repository.cam.ac.uk/handle/1810/363032
https://doi.org/10.1093/nar/gkad1005
https://www.repository.cam.ac.uk/handle/1810/364488
https://doi.org/10.1093/nar/gkad1005
https://www.repository.cam.ac.uk/handle/1810/367641
https://doi.org/10.1093/nar/gkad1005
https://www.repository.cam.ac.uk/handle/1810/364281
https://doi.org/10.1093/nar/gkad1005
https://www.repository.cam.ac.uk/handle/1810/365641
https://doi.org/10.1093/nar/gkad1005
https://www.repository.cam.ac.uk/handle/1810/378797
https://doi.org/10.1093/nar/gkad1005
https://discovery-pp.ucl.ac.uk/id/eprint/10189754/
https://escholarship.org/uc/item/7956s6h6
https://escholarship.org/content/qt7956s6h6/qt7956s6h6.pdf
Rights: CC BY
URL: http://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Přístupové číslo: edsair.doi.dedup.....cf4363f7ffbbda68bc01b96327bdd842
Databáze: OpenAIRE
Popis
Abstrakt: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.
ISSN:13624962
03051048
DOI:10.1093/nar/gkad1005