2021
TITAN: T-cell receptor specificity prediction with bimodal attention networks
Weber A, Born J, Martínez M. TITAN: T-cell receptor specificity prediction with bimodal attention networks. Bioinformatics 2021, 37: i237-i244. PMID: 34252922, PMCID: PMC8275323, DOI: 10.1093/bioinformatics/btab294.Peer-Reviewed Original ResearchConceptsK-nearest neighborAttention networkLeverage transfer learningState-of-the-artK-nearest-neighbor (KNN) classifierInput data spaceK-NN classifierBimodal neural networkSMILES sequencesTransfer learningData augmentationAttention heatmapsCompetitive performanceNeural networkData spaceT cell receptorBoost performanceT-cell receptor sequencingClassifierNetworkImproved performanceT cellsPrediction of specificityPerformanceSequencing of T-cell receptor
2019
Toward Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-Based Convolutional Encoders
Manica M, Oskooei A, Born J, Subramanian V, Sáez-Rodríguez J, Martínez M. Toward Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-Based Convolutional Encoders. Molecular Pharmaceutics 2019, 16: 4797-4806. PMID: 31618586, DOI: 10.1021/acs.molpharmaceut.9b00520.Peer-Reviewed Original ResearchConceptsConvolutional encoderReceptor tyrosine kinasesProtein-protein interaction networkAttention-based encoderStructural similarity indexSelection of encodingDrug designDrug sensitivity predictionGene expression profilesIn silico predictionSensitivity predictionAttention weightsLeukemia cell linesSMILES sequencesInformative genesGene expression profiles of tumorsApoptotic processInteraction networkExpression profiles of tumorsBaseline modelIntracellular interactionsEncodingTyrosine kinaseDevelopment of personalized therapiesGenes