NetTCR-2.0 enables accurate prediction of TCR-peptide binding by using paired TCRα and β sequence data
Montemurro et al. present NetTCR-2.0, a convolutional neural network-based tool for predicting the interactions between T cell receptors and MHC-peptide complexes. This tool demonstrates that the best predictions are made when CDR3 α or CDR3 β binding data are used in combination.
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Autores principales: | Alessandro Montemurro, Viktoria Schuster, Helle Rus Povlsen, Amalie Kai Bentzen, Vanessa Jurtz, William D. Chronister, Austin Crinklaw, Sine R. Hadrup, Ole Winther, Bjoern Peters, Leon Eyrich Jessen, Morten Nielsen |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/0fd24268ab1c4d9e95f4d96aaa1b710a |
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