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Paper Details

Representing glycophenotypes: semantic unification of glycobiology resources for disease discovery.
Database (Oxford)
5
2019
HPO, Human, carbohydrates, glycan-related diseases, patients, rare diseases
Animals, Disease, Glycomics, Humans, Knowledge Bases, Phenotype, Polysaccharides, Semantics
Author NameAffiliation
Jean-Philippe GourdineOregon Clinical & Translational Research Institute, Oregon Health & Science University
Jean-Philippe GourdineOregon Health & Science University Library
Jean-Philippe Gourdine
Matthew H BrushOregon Clinical & Translational Research Institute, Oregon Health & Science University
Matthew H Brush
Matthew H BrushOregon Clinical & Translational Research Institute, Oregon Health & Science University
Matthew H Brush
Nicole VasilevskyOregon Clinical & Translational Research Institute, Oregon Health & Science University
Nicole Vasilevsky
Nicole VasilevskyOregon Clinical & Translational Research Institute, Oregon Health & Science University
Nicole Vasilevsky
Kent Shefchek
Kent ShefchekLinus Pauling Institute, Oregon State University
Kent Shefchek
Kent ShefchekLinus Pauling Institute, Oregon State University
Sebastian K??hler
Sebastian K??hlerCharite Centrum fur Therapieforschung, Charite-Universitatsmedizin Berlin Corporate Member of Freie Universitat Berlin, Humboldt-Universitat zu Berlin and Berlin Institute of Health
Sebastian K??hler
Sebastian K??hlerCharite Centrum fur Therapieforschung, Charite-Universitatsmedizin Berlin Corporate Member of Freie Universitat Berlin, Humboldt-Universitat zu Berlin and Berlin Institute of Health
Nicolas Matentzoglu
Nicolas MatentzogluEuropean Bioinformatics Institute (EMBL-EBI)
Monica C Munoz-Torres
Monica C Munoz-TorresLinus Pauling Institute, Oregon State University
Julie A McMurry
Julie A McMurryLinus Pauling Institute, Oregon State University
Julie A McMurry
Julie A McMurryLinus Pauling Institute, Oregon State University
Xingmin Aaron Zhang
Xingmin Aaron Zhang
Peter N Robinson
Peter N Robinson
Peter N Robinson
Peter N Robinson
Melissa A HaendelOregon Clinical & Translational Research Institute, Oregon Health & Science University
Melissa A Haendel
Melissa A HaendelLinus Pauling Institute, Oregon State University
Melissa A HaendelOregon Clinical & Translational Research Institute, Oregon Health & Science University
Melissa A Haendel
Melissa A HaendelLinus Pauling Institute, Oregon State 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
Human Phenotype OntologyStandardized vocabulary of phenotypic abnormalities in human diseaseLink
Human Phenotype OntologyStandardized vocabulary of phenotypic abnormalities in human diseaseLink
Human Phenotype OntologyStandardized vocabulary of phenotypic abnormalities in human diseaseLink