The Human Phenotype Ontology in 2024: phenotypes around the world
Copyright policy )The Human Phenotype Ontology in 2024: phenotypes around the world
Abstract 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.
- UNSW Sydney Australia
- University of Pittsburgh United States
- Tilburg University Netherlands
- Osakidetza Spain
- Institute of Research and Innovation Parc Tauli Spain
Human Genetics - Radboud University Medical Center - DCMN, 3105 Genetics (for-2020), 34 Chemical sciences (for-2020), 31 Biological sciences (for-2020), Machine Learning and Artificial Intelligence, Database Issue, anzsrc-for: 31 Biological Sciences, Developmental Biology (science-metrix), Humans (mesh), Networking and Information Technology R&D (NITRD) (rcdc), 3 Good Health and Well Being (sdg), JGM, Generic health relevance (hrcs-hc), 3 Good Health and Well Being, 600, Genomics, Biological Sciences, Rare diseases, Phenotype (mesh), 06 Biological Sciences (for), anzsrc-for: 41 Environmental sciences, Phenotype, Networking and Information Technology R&D (NITRD), Rare Diseases (mesh), Machine Learning and Artificial Intelligence (rcdc), Algorithms, 610, 08 Information and Computing Sciences (for), 3105 Genetics, Biological Ontologies (mesh), Rare Diseases, anzsrc-for: 34 Chemical sciences, Information and Computing Sciences, Genetics, Humans, Algorithms (mesh), JMG, 31 Biological Sciences (for-2020), Genetics (rcdc), Human Genome, 4.1 Discovery and preclinical testing of markers and technologies (hrcs-rac), anzsrc-for: 05 Environmental Sciences, Human Genome (rcdc), 4.1 Discovery and preclinical testing of markers and technologies, anzsrc-for: 3105 Genetics, Good Health and Well Being, Chemical sciences, Biological Ontologies, 41 Environmental sciences (for-2020), Genomics (mesh), anzsrc-for: 06 Biological Sciences, Generic health relevance, anzsrc-for: 08 Information and Computing Sciences, Biological ontologies, Environmental Sciences, 05 Environmental Sciences (for), 31 Biological Sciences, Developmental Biology
Human Genetics - Radboud University Medical Center - DCMN, 3105 Genetics (for-2020), 34 Chemical sciences (for-2020), 31 Biological sciences (for-2020), Machine Learning and Artificial Intelligence, Database Issue, anzsrc-for: 31 Biological Sciences, Developmental Biology (science-metrix), Humans (mesh), Networking and Information Technology R&D (NITRD) (rcdc), 3 Good Health and Well Being (sdg), JGM, Generic health relevance (hrcs-hc), 3 Good Health and Well Being, 600, Genomics, Biological Sciences, Rare diseases, Phenotype (mesh), 06 Biological Sciences (for), anzsrc-for: 41 Environmental sciences, Phenotype, Networking and Information Technology R&D (NITRD), Rare Diseases (mesh), Machine Learning and Artificial Intelligence (rcdc), Algorithms, 610, 08 Information and Computing Sciences (for), 3105 Genetics, Biological Ontologies (mesh), Rare Diseases, anzsrc-for: 34 Chemical sciences, Information and Computing Sciences, Genetics, Humans, Algorithms (mesh), JMG, 31 Biological Sciences (for-2020), Genetics (rcdc), Human Genome, 4.1 Discovery and preclinical testing of markers and technologies (hrcs-rac), anzsrc-for: 05 Environmental Sciences, Human Genome (rcdc), 4.1 Discovery and preclinical testing of markers and technologies, anzsrc-for: 3105 Genetics, Good Health and Well Being, Chemical sciences, Biological Ontologies, 41 Environmental sciences (for-2020), Genomics (mesh), anzsrc-for: 06 Biological Sciences, Generic health relevance, anzsrc-for: 08 Information and Computing Sciences, Biological ontologies, Environmental Sciences, 05 Environmental Sciences (for), 31 Biological Sciences, Developmental Biology
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