NetTCR-2.0 enables accurate prediction of TCR-peptide binding by using paired TCRα and β sequence data

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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Detalles Bibliográficos
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
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
Biology (General)
QH301-705.5
Acceso en línea:https://doaj.org/article/0fd24268ab1c4d9e95f4d96aaa1b710a
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https://doaj.org/article/0fd24268ab1c4d9e95f4d96aaa1b710a

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