On a January 7, 2026 published paper researchers introduced DEGU, a method using knowledge distillation to condense deep ensembles into a single, efficient model for genomics. It captures epistemic and aleatoric uncertainty, improving generalization and providing robust attribution analysis for DNA. Source: January 07 2026 Uncertainty-aware genomic deep learning with knowledge distillation Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory Jessica Zhou, Kaeli Rizzo, Trevor Christensen, Ziqi Tang, Peter K. Koo https://doi.org/10.1038/s44387-025-00053-3