Ning Li

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.

The paper evaluates open search methods for identifying modified peptides through simulations and proposes an analytical model to quantify performance based on spectrum quality and PTM count.

ECL 2.0 improves peptide-peptide pair identification by achieving linear complexity and better sensitivity compared to existing tools.

PIPI improves PTM-invariant peptide identification by using Boolean coding and dynamic programming, achieving higher sensitivity and speed compared to existing tools.