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.

Our team is located at the University of North Carolina at Chapel Hill · Berlin Institute of Health at Charité · The Jackson Laboratory · Lawrence Berkeley National Laboratory· Queen Mary University of London · Renaissance Computing Institute · European Bioinformatics Institute · Semanticly · Ada Health · University of Colorado

The Monarch Initiative

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The Monarch Initiative

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