End-to-end deep learning methods for genetic risk prediction of schizophrenia
Nature
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Researchers applied end-to-end neural network models to whole exome sequencing data from over 12,000 individuals, improving schizophrenia risk prediction by capturing complex genetic interactions beyond linear models. Their approach also identified known and potential new risk genes, including BASP1.
