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
2020
FPGA Accelerated Analysis of Boolean Gene Regulatory Networks
Manica M, Polig R, Purandare M, Mathis R, Hagleitner C, Martínez M. FPGA Accelerated Analysis of Boolean Gene Regulatory Networks. IEEE/ACM Transactions On Computational Biology And Bioinformatics 2020, 17: 2141-2147. PMID: 31494553, DOI: 10.1109/tcbb.2019.2936836.Peer-Reviewed Original ResearchConceptsQualitative models of gene regulatory networksModels of gene regulatory networksAdvanced high-throughput technologiesGene regulatory networksHigh-throughput technologiesComplex molecular networkBoolean modelRegulatory networksBiological insightsT-cell large granular lymphocytic leukemiaMolecular networksAttractor detectionField Programmable Gate ArrayLarge granular lymphocytic leukemiaSoftware simulation toolGranular lymphocytic leukemiaSimulation toolPerformance improvementReconfigurable integrated circuits