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Paper Details

Biolink Model: A universal schema for knowledge graphs in clinical, biomedical, and translational science.
Clin Transl Sci
28
2022
Biolink, KGs, biomedical KGs, gene
Knowledge, Pattern Recognition, Automated, Translational Science, Biomedical
Author NameAffiliation
Deepak R Unni
Deepak R UnniLawrence Berkeley National Laboratory
Sierra A T MoxonLawrence Berkeley National Laboratory
Michael BadaCenter for Health AI, University of Colorado Anschutz Medical Campus
Matthew H BrushCenter for Health AI, University of Colorado Anschutz Medical Campus
Matthew H BrushCenter for Health AI, University of Colorado Anschutz Medical Campus
Richard Bruskiewich
Paul A ClemonsLawrence Berkeley National Laboratory
Paul A ClemonsLawrence Berkeley National Laboratory
Vlado Dan????kBroad Institute
Michel DumontierBroad Institute
Michel DumontierBroad Institute
Karamarie FechoInstitute of Data Science, Maastricht University
Gustavo GlusmanRenaissance Computing Institute, University of North Carolina at Chapel Hill
Jennifer J HadlockInstitute for Systems Biology
Nomi L HarrisInstitute for Systems Biology
Nomi L HarrisInstitute for Systems Biology
Nomi L HarrisLawrence Berkeley National Laboratory
Tim PutmanInstitute for Systems Biology
Guangrong QinCenter for Health AI, University of Colorado Anschutz Medical Campus
Stephen A RamseyInstitute for Systems Biology
Kent ShefchekOregon State University
Kent ShefchekOregon State University
Cui TaoCenter for Health AI, University of Colorado Anschutz Medical Campus
Karthik SomanJohns Hopkins University
Karthik SomanUniversity of California San Francisco
Melissa A HaendelCenter for Health AI, University of Colorado Anschutz Medical Campus
Melissa A HaendelCenter for Health AI, University of Colorado Anschutz Medical Campus
Chris BizonCenter for Health AI, University of Colorado Anschutz Medical Campus
Chris BizonCenter for Health AI, University of Colorado Anschutz Medical Campus
Christopher J MungallRenaissance Computing Institute, University of North Carolina at Chapel Hill
Christopher J MungallRenaissance Computing Institute, University of North Carolina at Chapel Hill
Christopher J MungallLawrence Berkeley National Laboratory
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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