BioinformaticseLifePeer-reviewed
NetTCR 2.2 - Improved TCR specificity predictions by combining pan- and peptide-specific training strategies, loss-scaling and integration of sequence similarity
Mathias Fynbo Jensen, Morten Nielsen
NetTCR 2.2 improves TCR specificity predictions by combining pan- and peptide-specific training, loss-scaling, and sequence similarity integration, achieving state-of-the-art performance on the IMMREP 2022 benchmark.
2 citations