Article

Mapping Genetic Risk Associations to Cellular Contexts via Deep Learning and Biological Ontologies

2026-05-28

Abstract excerpt

Translating genome-wide association studies (GWAS) signals into trait-relevant cellular contexts remains challenging due to the complexity of the genomic regulatory code and linkage disequilibrium among associated variants. We present a novel computational framework that aggregates deep learning–based predictions of the functional effects of noncoding variants on transcriptional regulatory elements across GWAS loc...

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Literature Corpus work: c9462b7b-41fc-5737-bc31-63c0bcc726e2
DOI: 10.64898/2026.05.25.726449

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