3 papers
cs.LG2026
Central Dogma Transformer III: Interpretable AI Across DNA, RNA, and Protein
Nobuyuki Ota
Biological AI models increasingly predict complex cellular responses, yet their learned representations remain disconnected from the molecular processes they aim to capture. We pre…
cs.LG2026
Central Dogma Transformer II: An AI Microscope for Understanding Cellular Regulatory Mechanisms
Nobuyuki Ota
Motivation: Interpretability is not optional in biology: understanding gene regulation requires models whose learned structure can be directly interrogated, not merely accurate pre…
cs.LG2026
Central Dogma Transformer: Towards Mechanism-Oriented AI for Cellular Understanding
Nobuyuki Ota
Understanding cellular mechanisms requires integrating information across DNA, RNA, and protein - the three molecular systems linked by the Central Dogma of molecular biology. Whil…