Saghar Kaabinejadian

NetMHCIIphosPan predicts HLA class II antigen presentation of phosphorylated peptides using immunopeptidomics data, outperforming existing tools.

The paper improves HLA-DQ antigen presentation prediction using machine learning and shows trans-only variants have limited impact on the immunopeptidome.

The paper shows that neopeptide immunogenicity is influenced by the subcellular location of their parent proteins, improving predictions of vaccine and immunotherapy responses.

The paper improves MHC II epitope prediction by integrating mass spectrometry data with a new machine learning framework, achieving better performance than existing methods.