Article

DeepTCR: a deep learning framework for understanding T-cell receptor sequence signatures within complex T-cell repertoires

2018-11-07

Abstract excerpt

Deep learning algorithms have been utilized to achieve enhanced performance in pattern-recognition tasks, such as in image and vocal recognition 1,2 . The ability to learn complex patterns in data has tremendous implications in the genomics and immunology worlds, where sequence motifs become learned ‘features’ that can be used to predict functionality, guiding our understanding of disease and basic biology 3–6 ....

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 09f585a1-efb8-5b6b-9be3-ee0041dc807b
DOI: 10.1101/464107

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

DeepTCR: a deep learning framework for understanding T-cell receptor sequence signatures within complex T-cell repertoiresDOI 10.1101/464107Read

BenchRep-T: A Systematic Evaluation of T-Cell Repertoire-Based Disease DiagnosticsSemantic proximity Read

Disease associated human TCR characterization by deep-learning framework TCR-DeepInsightSemantic proximity Read

TCR-BERT: learning the grammar of T-cell receptors for flexible antigen-xbinding analysesSemantic proximity Read

DeepLION2: deep multi-instance contrastive learning framework enhancing the prediction of cancer-associated T cell receptors by attention strategy on motifsSemantic proximity Read

TCRconv: predicting recognition between T cell receptors and epitopes using contextualized motifsSemantic proximity Read

THLANet: A Deep Learning Framework for Predicting TCR-pHLA Binding in Immunotherapy ApplicationsSemantic proximity Read

Improved Deep Learning Prediction of TCR-HLA AssociationsSemantic proximity Read

Predicting recognition between T cell receptors and epitopes using contextualized motifsSemantic proximity Read

NetTCR: sequence-based prediction of TCR binding to peptide-MHC complexes using convolutional neural networksSemantic proximity Read

Detection of Enriched T Cell Epitope Specificity in Full T Cell Receptor Sequence RepertoiresSemantic proximity Read

Neural Network Models for Sequence-Based TCR and HLA Association PredictionSemantic proximity Read

T-Cell Receptor Repertoire Sequencing in the Era of Cancer ImmunotherapySemantic proximity Read