Article

Learning Minimal Gene Programs for Disease-Aligned Representations

2026-07-22

Abstract excerpt

Identifying small, interpretable gene sets that robustly capture disease-associated variation in singlecell transcriptomic data remains a central challenge for biological interpretation and experimental followup. In practice, commonly used differential expression and sparsity-based approaches often produce large, unstable gene lists that fail to generalize across patients due to strong donor-specific confounding....

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Literature Corpus work: 6e7b9ee6-fdd2-585f-8cc3-89e5f673c8a5
DOI: 10.64898/2026.07.17.739212

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