Our broad goal is to better understand how genetic variation leads to phenotypic variation for complex traits including disease susceptibility and drug response. We develop systems approaches to complex trait prediction by building computational models that leverage and integrate similarity in genetic, transcriptomic, proteomic, or other omics-level data. Our current focus is developing methods that better identify causal DNA variation across populations to better understand genetic risk and underlying mechanisms of disease.

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