Tianchi Lu

TriStageHLA improves epitope prioritization by integrating peptide screening, binding prediction, and immunogenicity assessment with high accuracy and efficiency.

This paper introduces PHbinder and PSGM, models that predict epitopes and identify HLA-I alleles, achieving high accuracy and uncovering new alleles.

The paper introduces PhosF3C, a model combining a fine-tuned protein language model and conformer architecture to predict phosphorylation sites with high accuracy.

TransHLA predicts epitopes across all HLA alleles with high accuracy, outperforming existing models in specificity and sensitivity for immunogenic and neoepitope identification.