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Paper Details

The Monarch Initiative in 2024: an analytic platform integrating phenotypes, genes and diseases across species.
Nucleic Acids Res
4
2024
Monarch, genes, patient
Author NameAffiliation
Tim E PutmanUniversity of Colorado Anschutz Medical Campus
Kevin SchaperUniversity of Colorado Anschutz Medical Campus
Nicolas Matentzoglu
Vincent P RubinettiUniversity of Colorado Anschutz Medical Campus
Faisal S AlquaddoomiUniversity of Colorado Anschutz Medical Campus
Corey CoxUniversity of Colorado Anschutz Medical Campus
John Harry CaufieldLawrence Berkeley National Laboratory
John Harry CaufieldLawrence Berkeley National Laboratory
Glass ElsarboukhUniversity of Colorado Anschutz Medical Campus
Sarah GehrkeUniversity of Colorado Anschutz Medical Campus
Harshad HegdeLawrence Berkeley National Laboratory
Ian BraunCritical Path Institute
Richard M BruskiewichDelphinai Corporation
Luca CappellettiUniversity of Fribourg
Seth CarbonLawrence Berkeley National Laboratory
Anita R CaronEuropean Bioinformatics Institute (EMBL-EBI)
Lauren E ChanCollege of Public Health and Human Sciences, Oregon State University
Christopher G ChuteJohns Hopkins University
Katherina G CortesUniversity of Colorado Anschutz Medical Campus
Vin??cius De SouzaEuropean Bioinformatics Institute (EMBL-EBI)
Tommaso FontanaUniversita degli Studi di Milano Statale
Nomi L HarrisLawrence Berkeley National Laboratory
Nomi L HarrisLawrence Berkeley National Laboratory
Emily L HartleyCritical Path Institute
Eric HurwitzUniversity of Colorado Anschutz Medical Campus
Julius O B JacobsenWilliam Harvey Research Institute, Queen Mary University of London
Madan KrishnamurthyUniversity of Colorado Anschutz Medical Campus
Bryan LarawayUniversity of Colorado Anschutz Medical Campus
James A McLaughlinEuropean Bioinformatics Institute (EMBL-EBI)
Julie A McMurryUniversity of Colorado Anschutz Medical Campus
Julie A McMurryUniversity of Colorado Anschutz Medical Campus
Sierra A T MoxonLawrence Berkeley National Laboratory
Kathleen R MullenUniversity of Colorado Anschutz Medical Campus
Shawn T O'NeilUniversity of Colorado Anschutz Medical Campus
Kent ShefchekUniversity of Colorado Anschutz Medical Campus
Kent ShefchekUniversity of Colorado Anschutz Medical Campus
Ray StefancsikEuropean Bioinformatics Institute (EMBL-EBI)
Sabrina ToroUniversity of Colorado Anschutz Medical Campus
Nicole VasilevskyCritical Path Institute
Nicole VasilevskyCritical Path Institute
Ramona L WallsCritical Path Institute
Patricia L WhetzelUniversity of Colorado Anschutz Medical Campus
Patricia L WhetzelUniversity of Colorado Anschutz Medical Campus
David Osumi-SutherlandEuropean Bioinformatics Institute (EMBL-EBI)
David Osumi-SutherlandEuropean Bioinformatics Institute (EMBL-EBI)
Damian SmedleyWilliam Harvey Research Institute, Queen Mary University of London
Peter N Robinson
Christopher J MungallLawrence Berkeley National Laboratory
Christopher J MungallLawrence Berkeley National Laboratory
Melissa A HaendelUniversity of Colorado Anschutz Medical Campus
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Datasets

Monarch InitiativeThe Monarch Initiative is an integrative data and analytic platform connecting phenotypes to genotypes across species, bridging basic and applied research with semantics-based analysis. The correlation of phenotypic outcomes and disease with genetic variation and environmental factors is a core pursuit in biology and biomedicine. We have created or currently contribute to many essential bio-ontologies that together enable sophisticated and semantically integrated computational analysis across gene, genotype, variant, disease, and phenotype data. We have developed algorithms and tools that are in use by multiple communities for tasks including the identification of animal models of human disease through phenotypic similarity, phenotype-driven computational support for differential diagnostics, and translational research.Link
Monarch InitiativeHuman disease-related phenotypes in model organismsLink
Monarch InitiativeThe Monarch Initiative is an integrative data and analytic platform connecting phenotypes to genotypes across species, bridging basic and applied research with semantics-based analysis. The correlation of phenotypic outcomes and disease with genetic variation and environmental factors is a core pursuit in biology and biomedicine. We have created or currently contribute to many essential bio-ontologies that together enable sophisticated and semantically integrated computational analysis across gene, genotype, variant, disease, and phenotype data. We have developed algorithms and tools that are in use by multiple communities for tasks including the identification of animal models of human disease through phenotypic similarity, phenotype-driven computational support for differential diagnostics, and translational research.Link
Monarch InitiativeThe Monarch Initiative is an integrative data and analytic platform connecting phenotypes to genotypes across species, bridging basic and applied research with semantics-based analysis. The correlation of phenotypic outcomes and disease with genetic variation and environmental factors is a core pursuit in biology and biomedicine. We have created or currently contribute to many essential bio-ontologies that together enable sophisticated and semantically integrated computational analysis across gene, genotype, variant, disease, and phenotype data. We have developed algorithms and tools that are in use by multiple communities for tasks including the identification of animal models of human disease through phenotypic similarity, phenotype-driven computational support for differential diagnostics, and translational research.Link
Monarch InitiativeThe Monarch Initiative is an integrative data and analytic platform connecting phenotypes to genotypes across species, bridging basic and applied research with semantics-based analysis. The correlation of phenotypic outcomes and disease with genetic variation and environmental factors is a core pursuit in biology and biomedicine. We have created or currently contribute to many essential bio-ontologies that together enable sophisticated and semantically integrated computational analysis across gene, genotype, variant, disease, and phenotype data. We have developed algorithms and tools that are in use by multiple communities for tasks including the identification of animal models of human disease through phenotypic similarity, phenotype-driven computational support for differential diagnostics, and translational research.Link
Monarch InitiativeThe Monarch Initiative is an integrative data and analytic platform connecting phenotypes to genotypes across species, bridging basic and applied research with semantics-based analysis. The correlation of phenotypic outcomes and disease with genetic variation and environmental factors is a core pursuit in biology and biomedicine. We have created or currently contribute to many essential bio-ontologies that together enable sophisticated and semantically integrated computational analysis across gene, genotype, variant, disease, and phenotype data. We have developed algorithms and tools that are in use by multiple communities for tasks including the identification of animal models of human disease through phenotypic similarity, phenotype-driven computational support for differential diagnostics, and translational research.Link
Monarch InitiativeHuman disease-related phenotypes in model organismsLink
Monarch InitiativeHuman disease-related phenotypes in model organismsLink
Monarch InitiativeThe Monarch Initiative is an integrative data and analytic platform connecting phenotypes to genotypes across species, bridging basic and applied research with semantics-based analysis. The correlation of phenotypic outcomes and disease with genetic variation and environmental factors is a core pursuit in biology and biomedicine. We have created or currently contribute to many essential bio-ontologies that together enable sophisticated and semantically integrated computational analysis across gene, genotype, variant, disease, and phenotype data. We have developed algorithms and tools that are in use by multiple communities for tasks including the identification of animal models of human disease through phenotypic similarity, phenotype-driven computational support for differential diagnostics, and translational research.Link
Monarch InitiativeThe Monarch Initiative is an integrative data and analytic platform connecting phenotypes to genotypes across species, bridging basic and applied research with semantics-based analysis. The correlation of phenotypic outcomes and disease with genetic variation and environmental factors is a core pursuit in biology and biomedicine. We have created or currently contribute to many essential bio-ontologies that together enable sophisticated and semantically integrated computational analysis across gene, genotype, variant, disease, and phenotype data. We have developed algorithms and tools that are in use by multiple communities for tasks including the identification of animal models of human disease through phenotypic similarity, phenotype-driven computational support for differential diagnostics, and translational research.Link
Monarch InitiativeHuman disease-related phenotypes in model organismsLink
Monarch InitiativeThe Monarch Initiative is an integrative data and analytic platform connecting phenotypes to genotypes across species, bridging basic and applied research with semantics-based analysis. The correlation of phenotypic outcomes and disease with genetic variation and environmental factors is a core pursuit in biology and biomedicine. We have created or currently contribute to many essential bio-ontologies that together enable sophisticated and semantically integrated computational analysis across gene, genotype, variant, disease, and phenotype data. We have developed algorithms and tools that are in use by multiple communities for tasks including the identification of animal models of human disease through phenotypic similarity, phenotype-driven computational support for differential diagnostics, and translational research.Link