Julien Racle

Capabilities, specificity gaps and training-data dependence of AlphaFold3 across diverse application areas

This paper evaluates AlphaFold3's performance across diverse structural biology tasks, finding uneven accuracy and strong dependence on training data.

Autophagy shapes the peptide repertoire of rheumatoid arthritis-associated HLA class II alleles

This study shows autophagy contributes to MHC class II presentation of RA-related peptides in HLA-DRB1*04:01 alleles, with 30% of peptides differing between autophagy sufficient and deficient cells.

Unpaired TCRα + TCRβ sequencing is sufficient for training machine learning TCR-epitope recognition predictors

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

Key determinants of T cell epitope recognition revealed by TCR specificity profiles

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.

Predicting MHC-I ligands across alleles and species: How far can we go?

This study evaluates how well MHC-I ligand predictions can be extrapolated across alleles and species using an improved predictor, finding high accuracy in human and mouse but lower in other species.

Robust estimation of cancer and immune cell-type proportions from bulk tumor ATAC-Seq data.

This paper develops EPIC-ATAC to estimate cancer and immune cell-type proportions from bulk tumor ATAC-Seq data, showing accurate prediction of immune contexture in breast cancer subtypes.

Community assessment of methods to deconvolve cellular composition from bulk gene expression

The paper evaluates deconvolution methods for inferring immune infiltration from bulk gene expression using a DREAM Challenge, finding that some community-contributed methods, especially deep learning-based ones, perform well.

Predictions of immunogenicity reveal potent SARS-CoV-2 CD8+ T-cell epitopes

The paper improves epitope prediction by integrating HLA-I ligand data and TCR recognition models, identifying potent SARS-CoV-2 CD8+ T-cell epitopes with experimental validation.