CLOOME: contrastive learning unlocks bioimaging databases for queries with chemical structures

Abstract

AbstractCurrently, bioimaging databases cannot be queried by chemical structures that induce the phenotypic effects captured by the image. We present a novel retrieval system based on contrastive learning that is able to identify the chemical structure inducing the phenotype out of ~2,000 candidates with a top-1 accuracy >70 times higher than a random baseline.