NetTCR-2.1: Lessons and guidance on how to develop models for TCR specificity predictions
Alessandro Montemurro(Technical University of Denmark), Morten Nielsen(Technical University of Denmark), Leon Eyrich Jessen(Technical University of Denmark)
Cited by 62
Related Papers
Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method
|BMC Bioinformatics|2007|621
NetTCR-2.0 enables accurate prediction of TCR-peptide binding by using paired TCRα and β sequence data
|Communications Biology|2021|262
Benchmarking solutions to the T-cell receptor epitope prediction problem: IMMREP22 workshop report
|ImmunoInformatics|2023|101
IMPROVE: a feature model to predict neoepitope immunogenicity through broad-scale validation of T-cell recognition
|Frontiers in Immunology|2024|26
Benchmarking solutions to the T-cell receptor epitope prediction problem: IMMREP22 workshop report
|bioRxiv (Cold Spring Harbor Laboratory)|2022|23