palermolab.com

Interpret-able-AI

Artificial intelligence is transforming the way we understand biology. At Interpret-able-AI, we develop computational methods that combine machine learning, molecular simulations, statistical physics, and mechanistic modeling to uncover the fundamental principles governing complex biomolecular systems.

Our vision is that AI should not simply predict outcomes—it should explain them.

Rather than treating biological systems as black boxes, we build interpretable computational frameworks that reveal the physical mechanisms underlying molecular function. These methods provide mechanistic insight, guide experimental design, and accelerate scientific discovery across structural biology, chemistry, and genome engineering.

Interpret-able-AI serves three complementary goals:

• Advance AI-enabled computational methodologies that address fundamental scientific questions.
• Make these methods accessible to researchers and students through tutorials, software, and educational resources.
• Build a collaborative community where computational scientists, experimentalists, and students can exchange ideas and develop the next generation of interpretable AI tools.

Whether you are a student taking your first steps in computational biology, an experimental scientist looking for mechanistic insight, or a computational researcher interested in developing new algorithms, we hope this platform will inspire new collaborations and discoveries.