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.

Bibliographic Details
Main Authors: 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
Format: Article
Language:English
Published: Nature Portfolio 2021-09-01
Series:Communications Biology
Online Access:https://doi.org/10.1038/s42003-021-02610-3

Internet

https://doi.org/10.1038/s42003-021-02610-3

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