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Central Dogma Transformer II: An AI Microscope for Understanding Cellular Regulatory Mechanisms

Ota, Nobuyuki
arXiv (OAI Expanded) · Papers
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machine-learningquantitative-methods
Motivation: Interpretability is not optional in biology: understanding gene regulation requires models whose learned structure can be directly interrogated, not merely accurate predictors whose internals resist mapping onto regulatory relationships. We ask whether an architecture mirroring the centr
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