National Human Genome Research Institute 5U01HG011967-05

Design, prediction, and prioritization of systematic perturbations of the human genome

This NIH grant awarded to Duke University supports the development of analytic tools and machine learning models to annotate and prioritize noncoding genetic variations for their functional and pathogenic impacts, advancing understanding of regulatory causes of disease.

Description

The project aims to develop analytic approaches and tools for the routine annotation of noncoding genetic variation for functionality and pathogenicity. It involves establishing best practices in perturbation assay design, developing machine learning models to predict the functional effects of noncoding variants, and identifying noncoding regions under functional constraint to prioritize variants for pathogenicity.

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