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Heterogeneous Network Edge Prediction: A Data Integration Approach to Prioritize Disease-Associated Genes

bioRxiv

Dec 11, 2014

Daniel S Himmelstein, Sergio E. Baranzini

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Abstract

The first decade of Genome Wide Association Studies (GWAS) has uncovered a wealth of disease-associated variants. Two important derivations will be the translation of this information into a multiscale understanding of pathogenic variants, and leveraging existing data to increase the po...read more

Mentioned in this Paper

Study
Anatomy, Regional
Anatomic Node
Research Personnel
MS gene
Biochemical Pathway
Disease Susceptibility
Genome-Wide Association Study
JAK2 protein, human
REL Protein
20
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  • Heterogeneous Network Edge Prediction: A Data Integration Approach to Prioritize Disease-Associated Genes

    bioRxiv

    Dec 11, 2014

    Daniel S Himmelstein, Sergio E. Baranzini

    PMID: 990011569

    DOI: 10.1101/011569

    Abstract

    The first decade of Genome Wide Association Studies (GWAS) has uncovered a wealth of disease-associated variants. Two important derivations will be the translation of this information into a multiscale understanding of pathogenic variants, and leveraging existing data to increase the po...read more

    Mentioned in this Paper

    Study
    Anatomy, Regional
    Anatomic Node
    Research Personnel
    MS gene
    20

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