Juliane Sarah Walz

This paper introduces Immunotype, a deep learning model that directly types HLA alleles from immunopeptidomics data with 87.2% accuracy.

The paper introduces t2pmhc, a structure-informed graph neural network for predicting TCR-pMHC binding, showing improved generalization to unseen peptides compared to existing methods.

This study uses ribosome profiling to identify conserved HIV-1 alternative open reading frames (ARFs) that encode T cell antigens, revealing new targets for vaccination.

TIMS2Rescore is a data-driven rescoring pipeline optimized for DDA-PASEF data that improves protein identification in proteomics analyses.

The paper presents the HLA Ligand Atlas, a resource of HLA-I and -II ligands from benign tissues, showing tissue and individual differences and non-canonical ligand origins.