2023
Chemical representation learning for toxicity prediction
Born J, Markert G, Janakarajan N, Kimber T, Volkamer A, Martínez M, Manica M. Chemical representation learning for toxicity prediction. Digital Discovery 2023, 2: 674-691. DOI: 10.1039/d2dd00099g.Peer-Reviewed Original ResearchChemical language modelsLanguage modelMolecular property prediction tasksMolecular property prediction modelProperty prediction tasksMolecular property predictionExplicit supervisionAttention weightsMultiscale convolutionData augmentationPrediction taskToxicity datasetMolecular representationsProperty prediction modelsImproved accuracyModel reliabilityDatasetProperty predictionChemical representationsToxicity predictionPrediction uncertaintyUncertainty estimationDrug discoveryRepresentationPrediction modelBenchmarking solutions to the T-cell receptor epitope prediction problem: IMMREP22 workshop report
Meysman P, Barton J, Bravi B, Cohen-Lavi L, Karnaukhov V, Lilleskov E, Montemurro A, Nielsen M, Mora T, Pereira P, Postovskaya A, Martínez M, Fernandez-de-Cossio-Diaz J, Vujkovic A, Walczak A, Weber A, Yin R, Eugster A, Sharma V. Benchmarking solutions to the T-cell receptor epitope prediction problem: IMMREP22 workshop report. ImmunoInformatics 2023, 9: 100024. DOI: 10.1016/j.immuno.2023.100024.Peer-Reviewed Original Research
2021
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