Baozhen Shan

DIAVariant identifies low abundance peptide variants from DIA-MS data without relying on reference databases, improving variant discovery while maintaining specificity.

The paper uses ZenoTOF mass spectrometry to analyze glycoproteomes from breast cancer and control samples, identifying 15 site-specific glycans as potential biomarkers for breast cancer detection.

NovoBoard evaluates de novo peptide sequencing methods using benchmark datasets and FDR estimation to assess accuracy and significance of peptide-spectrum matches.

This study introduces DeepNovo Peptidome and DeepSelf for neoantigen discovery and validation using immunopeptidomics and deep learning, demonstrating their application in cervical cancer tissues.

This paper introduces an immunopeptidomics workflow using PEAKS XPro to identify HLA-I ligands and neoantigens without relying on standard databases, revealing diverse peptides and mutations in colorectal cancer.

The paper evaluates DIA performance across multiple laboratories using standardized samples and provides benchmark datasets for education and tool development.

The paper introduces a personalized deep learning workflow to identify neoantigens from mass spectrometry data, improving accuracy and discovery rates in melanoma patients.