Stowers scientists develop a new way to visualize what AI models learn from DNA — and discover how to control what the models learn next

Stowers scientists develop a new way to visualize what AI models learn from DNA -- and discover how to control what the models learn next

PR Newswire

KANSAS CITY, Mo., Aug. 25, 2026

The AI model interpretation method, PISA, shows what genomic AI models learn, allowing scientists to separate experimental bias from biology, train more focused models, and uncover unexpected insights related to gene regulation and genetic disease.What's new, and why it matters:PISA (pairwise influence by sequence attribution) is a new method that traces a deep-learning model's prediction at any single DNA base back to every other base that influenced it, producing a base-pair-resolution map of what the model learned, not just what it predicted.Applying PISA to nucleosome mapping data, the team spotted and mathematically removed a technical bias baked into the data, revealing DNA sequences that position nucleosomes and, unexpectedly, mark the boundaries of larger 3D chromatin domains, normally identified only through expensive, sequencing-intensive methods.Biologists have long been interested in better understanding how specific DNA sequences relate to gene regulation and genetic disease. PISA can point to potential sequence elements and mechanisms that warrant further investigation.KANSAS CITY, Mo., Aug. 25, 2026 /PRNewswire/ -- Artificial intelligence can predict how a stretch of DNA will behave inside a cell. What it usually can't tell you is why it will behave that way. Researchers at the Stowers Institute for Medical Research have developed a new method that can.