SmilesGEN uses dual VAEs to jointly model drug structures and transcriptional responses, generating molecules with higher validity, novelty, and similarity to known ligands than prior methods.
A.; M \"u ller, K.-R.; and Tkatchenko, A
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Bridging the phenotype-target gap for molecular generation via multi-objective reinforcement learning
SmilesGEN uses dual VAEs to jointly model drug structures and transcriptional responses, generating molecules with higher validity, novelty, and similarity to known ligands than prior methods.