Modern biology is awash in data. Scientists can sequence DNA, track gene activity cell-by-cell, map proteins in space, and image tissues at microscopic resolution. However, it is a struggle to put all that information together to form a cohesive view.

A KAUST-led vision for artificial intelligence (AI) could help bridge that gap. An AI system that combines multiple biological data modalities into a single model has been described by members of the AI4BioMedicine lab in the Biomedical Division. Called a “super transformer”, the new AI architecture aims to turn today’s fragmented measurements by different technologies into a more coherent picture of life inside cells and tissues.

“This bridges the gaps between siloed computational approaches,” says Jesper Tegnér, professor of bioscience and computer science at KAUST who led the work.

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