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The Dey lab develops machine-learning and statistical models integrating genetic and genomic data to prioritize variants, genes, cell types underlying complex diseases, understand disease-specific regulatory architecture and build better patient risk score models

We leverage large-scale unbiased profiling including genomics, transcriptomics, proteomics to identify candidate oncogenes and proteins that are pathogenetically relevant in lymphoma.