AI Bio-Modeling Requires Understanding Regulatory Mechanisms
anshulkundaje · x · 2026-07-11
This response emphasizes that to truly advance AI x Biology, researchers must go beyond surface-level modeling. It requires rigorous experimental design and deep investigation into the cis / trans regulatory mechanisms that explain various perturbation effects. The author argues that for models to learn these phenomena and extrapolate effectively, these biological mechanisms must be integrated into the learning process.
They also point out that when perturbations push into highly "non-physiological" territories, they trigger incredibly "weird but beautiful" regulatory mechanisms. If the model hasn't implicitly learned these biophysical principles, reliable extrapolation becomes nearly impossible. Finally, they urge researchers at the intersection of AI and biology to deeply study differentiation, development, and artificial reprogramming, and to verify whether their models are actually encoding these mechanisms.
Related event: Stanford Professor Urges Deeper Mechanistic Understanding in AI Biology(2 posts)→
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