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A compendium of human gene functions derived from evolutionary modelling

39Citations signalées, ce qui n’est pas une note de qualité
56Institutions déclarées
12Pays d’affiliation déclarés

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Le résumé fourni par la source

Abstract A comprehensive, computable representation of the functional repertoire of all macromolecules encoded within the human genome is a foundational resource for biology and biomedical research. The Gene Ontology Consortium has been working towards this goal by generating a structured body of information about gene functions, which now includes experimental findings reported in more than 175,000 publications for human genes and genes in experimentally tractable model organisms1,2. Here, we describe the results of a large, international effort to integrate all of these findings to create a representation of human gene functions that is as complete and accurate as possible. Specifically, we apply an expert-curated, explicit evolutionary modelling approach to all human protein-coding genes. This approach integrates available experimental information across families of related genes into models that reconstruct the gain and loss of functional characteristics over evolutionary time. The models and the resulting set of 68,667 integrated gene functions cover approximately 82% of human protein-coding genes. The functional repertoire reveals a marked preponderance of molecular regulatory functions, and the models provide insights into the evolutionary origins of human gene functions. We show that our set of descriptions of functions can improve the widely used genomic technique of Gene Ontology enrichment analysis. The experimental evidence for each functional characteristic is recorded, thereby enabling the scientific community to help review and improve the resource, which we have made publicly available.

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Le contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
A compendium of human gene functions derived from evolutionary modelling
Date Crossref
26/02/2025
Éditeur
Springer Science and Business Media LLC
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.

Les institutions déclarées

SIB Swiss Institute of BioinformaticsUniversity of Southern CaliforniaLawrence Berkeley National LaboratoryStanford UniversityRenaissance Computing InstituteJackson LaboratoryCalifornia Institute of TechnologyRadboud University NijmegenRadboud University Medical CenterRadboud Institute for Molecular Life SciencesTexas A&M UniversityNorthwestern UniversityUniversity of Maryland, BaltimoreUniversity of CambridgeUniversity College LondonNew York UniversityMedical College of WisconsinUniversity of LausanneUniversität HamburgUniversity Medical Center Hamburg-EppendorfUniversity of Rome Tor VergataUniversitat Autònoma de BarcelonaHospital de Sant PauInstitut de Recerca Sant PauYale UniversityMax Planck Institute for Multidisciplinary SciencesAgency for Science, Technology and ResearchNational University of SingaporeInstitute of Molecular and Cell BiologyAmsterdam NeuroscienceSorbonne UniversitéInstitut du CerveauJohns Hopkins UniversityDiscovery InstituteLeibniz Institute for NeurobiologyUniversity of CopenhagenMax Planck Institute for Biophysical ChemistryKorea Advanced Institute of Science and TechnologyHarvard UniversityVrije Universiteit AmsterdamLeibniz-Forschungsinstitut für Molekulare PharmakologieUtrecht UniversityMontreal Neurological Institute and HospitalMcGill UniversityUniversity of SouthamptonOtto-von-Guericke-Universität MagdeburgCornell UniversityWeill Cornell MedicineNeuroscience InstituteBroad InstituteMassachusetts Institute of TechnologyCenter for Behavioral Brain SciencesPhoenix BioinformaticsEuropean Bioinformatics InstituteCincinnati Children's Hospital Medical CenterUniversity of Oregon

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Les sujets associés

Bioinformatics and Genomic NetworksBiomedical Text Mining and OntologiesGenomics and Phylogenetic Studies

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