MATE-Pred: Multimodal Attention-based TCR-Epitope interaction Predictor
MATE-Pred: Multimodal Attention-based TCR-Epitope interaction Predictor
An accurate binding affinity prediction between T-cell receptors and epitopes contributes decisively to develop successful immunotherapy strategies. Some state-of-the-art computational methods implement deep learning techniques by integrating evolutionary features to convert the amino acid residues of cell receptors and epitope sequences into numerical values, while some other methods employ pre-trained …