Nicola Ternette

Simplifying principles underlying the highly complex peptide motif of the promiscuous chicken class I molecule, BF2*21:01

The paper identifies simplifying principles governing peptide binding by the promiscuous chicken class I molecule BF2*21:01, revealing patterns that enable broad peptide repertoire while maintaining stable binding.

Coxsackievirus B Escapes Antiviral CD8⁺ T Cells but Triggers Robust CD4⁺ Memory Responses

This study shows that Coxsackievirus B3 evades CD8+ T-cell immunity by downregulating HLA Class I and viral peptide presentation, while inducing robust CD4+ T-cell responses and memory formation.

High-quality peptide evidence for annotating non-canonical open reading frames as human proteins

The paper identifies 25% of 7,264 non-canonical open reading frames (ncORFs) as producing translated gene products, supported by over 3,000 peptides from 3.8 billion mass spectra.

NetMHCIIphosPan: a machine learning tool for predictingHLA class II antigen presentation of phosphorylated peptides.

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

Autoimmune interactions between the HLA-DQβ157 polymorphism, T cell receptors, and microbial mimics of insulin in type 1 diabetes

The paper investigates how HLA-DQβ157 polymorphism influences T cell receptor selection and links it to microbial antigens that mimic insulin, contributing to type 1 diabetes pathogenesis.

Integral use of immunopeptidomics and immunoinformatics for the characterization of antigen presentation and rational identification of BoLA-DR-presented peptides and epitopes

The paper integrates immunopeptidomics and immunoinformatics to characterize BoLA-DR antigen presentation and identify CD4 T cell epitopes with high predictive accuracy.

HLA binding of self-peptides is biased towards proteins with specific molecular functions

The paper shows HLA alleles preferentially present peptides from proteins with specific molecular functions, linking these preferences to HLA allele differences and disease susceptibility.

NNAlign_MA; MHC peptidome deconvolution for accurate MHC binding motif characterization and improved T cell epitope predictions

NNAlign_MA deconvolves poly-specific MHC peptidome data to accurately characterize binding motifs and improve T cell epitope predictions.