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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...
Autores principales: | Ye, Yilin, Wang, Jian, Xu, Yunwan, Wang, Yi, Pan, Youdong, Song, Qi, Liu, Xing, Wan, Ji |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7787246/ https://www.ncbi.nlm.nih.gov/pubmed/33407098 http://dx.doi.org/10.1186/s12859-020-03946-z |
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