Quantum-inspired generative machine learning over large datasets to infer new pleiotropic effects of genetic variants in multiple neuropsyciatric diseases
$144,180R01FY2018MHNIH
University Of Chicago, Chicago IL
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Abstract
Abstract In this supplement, we propose developing new computational approaches for psychiatric genetics, building on emergent strengths of deep learning and quantum computing. These approaches, utilizing very large external medical and genetic datasets, will allow automatic extension of the existing annotations of human genetic variants and of protein expression markers in brain to numerous under-studied neuropsychiatric diseases.
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