PaccMannRL: De novo generation of hit-like anticancer molecules from transcriptomic data via reinforcement learning
Born J, Manica M, Oskooei A, Cadow J, Markert G, Martínez M. PaccMannRL: De novo generation of hit-like anticancer molecules from transcriptomic data via reinforcement learning. IScience 2021, 24: 102269. PMID: 33851095, PMCID: PMC8022157, DOI: 10.1016/j.isci.2021.102269.Peer-Reviewed Original ResearchDrug designSimilarity to compoundsReinforcement learning methodDeep generative modelsDeep learning approachMolecular designStructurally similar to compoundsDrug-likenessComputational chemistryBridging systems biologyMolecule generationReinforcement learningReward functionLearning methodsGenerative modelLearning approachCompoundsAnticancer moleculesChemical propertiesMoleculesIncorporating informationCandidate drugsSynthesizabilityAnticancer drugsPrediction model
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