MATHLA: a robust framework for HLA-peptide binding prediction integrating bidirectional LSTM and multiple head attention mechanism
Background: Accurate prediction of binding between class I human leukocyte antigen (HLA) and neoepitope is critical for target identification within personalized T-cell based immunotherapy. Many recent prediction tools developed upon the deep learning algorithms and mass spectrometry data have indee...
Main Authors: | , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
BioMed Central Ltd
2021
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Subjects: | |
Online Access: | View Fulltext in Publisher |