Shuaijian Dai

This study identifies proteome-level amino acid substitutions in Alzheimer's disease using proteomic datasets and a specialized pipeline, revealing novel substitutions not detectable through genomic or transcriptomic methods.

The paper identifies WPRa4 and PMI4 as key proteins in Arabidopsis touch response, showing their role in mechano-sensing and calcium signaling through proteomic and transcriptomic analyses.

This study introduces a proteomic approach to identify amino acid substitutions in cancer, revealing novel substitutions and their roles in drug resistance and immune escape.

The paper identifies protein-protein interaction modules in mammalian cells using XL-MS data and bioinformatics, revealing hierarchical organization into compartments.

PIPI-C identifies PTM crosstalks in mass spectrometry data using a combinatorial optimization framework, revealing upregulated PTM patterns in cancer datasets.

This study introduces SeaPIC, an XL-MS tool for identifying post-translational modifications in protein-protein interactions and structures, successfully detecting previously undiscovered PTMs.

This paper introduces ECL-PF, a method for cleavable XL-MS data analysis that improves sensitivity in detecting protein-protein interactions and structures.

The paper introduces a pipeline called CHAMPION that uses qXL-MS and MONET modulomics to identify nuclear protein interactions and modules, revealing novel interactors and hormone-specific variants.