Kevin Yang

The paper develops a deep learning model that integrates multiple fragmentation techniques into standard LC-MS workflows, improving proteome coverage and identification rates.

diaTracer enables spectrum-centric analysis of diaPASEF proteomics data by generating pseudo-MS/MS spectra for direct peptide identification and quantification.

Koina provides an open-source, accessible ML/DL prediction service for proteomics, improving integration with existing tools like FragPipe.

MSBooster improves peptide identification rates by integrating deep learning-based features into existing workflows with MSFragger and Percolator.