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MUGO (Multi-head Genomic Optimization), an in silico perturbation framework that casts variant discovery as differentiable combinatorial optimization over genomic sequence, and MUGO-prioritized variants are enriched for GWAS signals across diverse tissues and a broad spectrum of complex traits.
Deciphering how non-coding variants perturb gene regulation is central to translating GWAS loci into mechanism, yet existing prioritization methods rarely deliver cell-type-resolved molecular effects, causal variant-to-gene attribution, or principled reasoning about combinatorial interactions. We introduce MUGO (Multi-...
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