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Paper Details

Navigating the Phenotype Frontier: The Monarch Initiative.
Genetics
49
2016
DNA
Computational Biology, Databases, Genetic, Genetic Association Studies, Genomics, Humans, Precision Medicine, Sequence Analysis, DNA, Sequence Analysis, Protein
Author NameAffiliation
Julie A McMurryand Oregon Health and Science University Library, Oregon Health and Science University
Julie A McMurryand Oregon Health and Science University Library, Oregon Health and Science University
Sebastian K??hlerInstitute for Medical Genetics and Human Genetics, Charite-Universitatsmedizin Berlin
Sebastian K??hlerInstitute for Medical Genetics and Human Genetics, Charite-Universitatsmedizin Berlin
Nicole L WashingtonLawrence Berkeley National Laboratory
Nicole L WashingtonLawrence Berkeley National Laboratory
James P Balhoff
James P Balhoff
Charles BorromeoUniversity of Pittsburgh
Matthew H Brushand Oregon Health and Science University Library, Oregon Health and Science University
Matthew H Brushand Oregon Health and Science University Library, Oregon Health and Science University
Seth CarbonLawrence Berkeley National Laboratory
Tom Conlinand Oregon Health and Science University Library, Oregon Health and Science University
Tom Conlinand Oregon Health and Science University Library, Oregon Health and Science University
Nathan DunnLawrence Berkeley National Laboratory
Mark E Engelstadand Oregon Health and Science University Library, Oregon Health and Science University
Mark E Engelstadand Oregon Health and Science University Library, Oregon Health and Science University
Erin Fosterand Oregon Health and Science University Library, Oregon Health and Science University
Erin Fosterand Oregon Health and Science University Library, Oregon Health and Science University
Jean-Philippe Gourdineand Oregon Health and Science University Library, Oregon Health and Science University
Julius O B JacobsenWellcome Trust Sanger Institute
Dan Keithand Oregon Health and Science University Library, Oregon Health and Science University
Bryan Larawayand Oregon Health and Science University Library, Oregon Health and Science University
Jeremy Nguyen-XuanLawrence Berkeley National Laboratory
Kent Shefchekand Oregon Health and Science University Library, Oregon Health and Science University
Kent Shefchekand Oregon Health and Science University Library, Oregon Health and Science University
Nicole Vasilevskyand Oregon Health and Science University Library, Oregon Health and Science University
Nicole Vasilevskyand Oregon Health and Science University Library, Oregon Health and Science University
Zhou YuanUniversity of Pittsburgh
Suzanna E LewisLawrence Berkeley National Laboratory
Suzanna E LewisLawrence Berkeley National Laboratory
Harry HochheiserUniversity of Pittsburgh
Tudor GrozaKinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research
Tudor GrozaKinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research
Damian SmedleyWilliam Harvey Research Institute, Barts and The London School of Medicine and Dentistry, and Queen Mary University of London
Peter N RobinsonInstitute for Medical Genetics and Human Genetics, Charite-Universitatsmedizin Berlin
Peter N RobinsonInstitute for Medical Genetics and Human Genetics, Charite-Universitatsmedizin Berlin
Christopher J MungallLawrence Berkeley National Laboratory
Christopher J MungallLawrence Berkeley National Laboratory
Melissa A Haendeland Oregon Health and Science University Library, Oregon Health and Science University
Melissa A Haendeland Oregon Health and Science University Library, Oregon Health and Science University
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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