2024
T-cell receptor binding prediction: A machine learning revolution
Weber A, Pélissier A, Martínez M. T-cell receptor binding prediction: A machine learning revolution. ImmunoInformatics 2024, 15: 100040. DOI: 10.1016/j.immuno.2024.100040.Peer-Reviewed Original ResearchProtein language modelsT cell receptorExtract biological insightsUnlabeled protein sequencesProtein sequencesBinding specificityBiological insightsProtein modelsRepertoire dataDeep learning modelsSequenceBlack-box modelsUnsupervised clustering approachDataset biasEvolution of computational modelsLack of generalityLanguage modelImmunizing sequencesMachine learning effortsCompetitive performanceOpaque modelsBiological propertiesLearning modelsClustering approachSupervised models
2022
DECODE: a computational pipeline to discover T cell receptor binding rules
Papadopoulou I, Nguyen A, Weber A, Martínez M. DECODE: a computational pipeline to discover T cell receptor binding rules. Bioinformatics 2022, 38: i246-i254. PMID: 35758821, PMCID: PMC9235487, DOI: 10.1093/bioinformatics/btac257.Peer-Reviewed Original ResearchConceptsT cell receptor bindingT cell receptorComputational pipelineTCR-epitope bindingBlack-box natureSequence motifsSequencing technologiesSupplementary dataBlack-box modelsBiochemical rulesMachine learningVisualization toolsComputational rulesDecodingData abundanceSequenceBioinformaticsEasy-to-useAdaptive immune responsesBindingBinding propertiesT cell-based therapiesT-cell receptor sequencingTCR bindingTCR specificity