A research team has developed DeepETD, an attention-based deep-learning model that predicts protein targets of endogenous metabolites by matching their disease associations, cellular phenotypes, and subcellular locations. 

Researchers have developed fluorescent molecules that permit imaging how DNA is packaged inside living cells at unprecedented resolution, and in preserved cells, close to the width of the double helix itself. The advance raises the possibility that one day they could train an AI to look at how DNA occupies three-dimensional space inside cells for diagnosing and treating cancer and other types of conditions.

Scientists from Gladstone Institutes, UC San Francisco, and Stanford University, in collaboration with Biohub, have unveiled a massive, high-resolution functional map of human immune cells that promises to transform our understanding of how genetics control health and disease. Published in the journal Cell, the study represents a landmark achievement in immunology and genomics. By systematically stress-testing genes across the genome in 22 million human immune cells, scientists moved beyond mere DNA sequencing to decode the dynamic circuits that govern how these genes actually work in the context of health and disease.