Congratulations to Kevin Yang, a PhD student in the Nesvizhskii lab, on developing a new computational tool, called MSBooster. Yang is first-author of a publication about this tool in Nature Communications.
MSBooster improves peptide and protein identification rates in proteomics by using deep learning-based predictions of peptides’ properties and their fragmentation spectra. In this article, MSBooster's application is illustrated using HLA immunopeptidomics, single-cell proteomics, and other datasets. This tool is fully integrated in the FragPipe computational platforms developed by the Nesvizhskii lab and that is used by thousands of scientists around the world to analyze mass spectrometry-based proteomics data.
Paper cited:
Yang, K.L., Yu, F., Teo, G.C. et al. MSBooster: improving peptide identification rates using deep learning-based features. Nat Commun 14, 4539 (2023). https://doi.org/10.1038/s41467-023-40129-9
Professor
PhD Student
