Dana Léa Moreno

This study shows that unpaired TCRα + TCRβ sequencing can train accurate TCR-epitope recognition predictors at lower cost than paired sequencing.

The paper quantifies how V and J gene usage affects CDR3 length and amino acid composition in TCR repertoires and provides a quality control framework for TCR sequencing data.

The paper introduces TCR specificity profiles to identify key determinants of TCR-epitope recognition and shows their ability to predict cross-reactivity and interpret machine learning models.

This paper introduces MixTCRpred, a deep learning model that predicts TCR-epitope interactions and identifies epitope-specific T cells, showing enrichment in COVID-19 patients.