Our lab focuses on 1) the development of computational methods and statistical models for analyzing mass spectrometric data (computational proteomics); 2) the development of novel algorithms and databases for cancer immunotherapy (immunopeptidomics); 3) the analysis of multi-omics profiling data for personalized medicine (multi-omics).
Selected Publications
•
X. Huang, et al., W. Shao# "The SysteMHC Atlas v2.0, an updated resource for mass spectrometry-based immunopeptidomics" Nucleic Acids Research 2024 (#独立通讯)
P. Forny*, X. Bonilla*, D. Lamparter*, W. Shao*, et al. “Integrated multi-omics reveals anaplerotic insufficiency in methylmalonyl-CoA mutase deficiency” Nature Metabolism 2023 (共一,按姓氏排列)
W. Shao, E. Caron, P. Pedrioli, R. Aebersold. “The SysteMHC Atlas: a Computational Pipeline, a Website, and a Data Repository for Immunopeptidomic Analyses” Methods in Molecular Biology. 2120:173-181 (2020) (一作;通讯)
W. Shao*, T. Guo*, N. Toussaint, U. Wagner, G. Ratsch, P. Wild, R. Aebersold et al. “Comparative analysis of mRNA degradation and protein degradation in 68 pairs of adjacent prostate tissue samples indicates high stability of proteins.” Nature Communications 10, 2524.
P. Forny*, X. Bonilla*, D. Lamparter*, W. Shao*, et al. “Integrated multi-omics reveals anaplerotic insufficiency in methylmalonyl-CoA mutase deficiency” Nature Metabolism 2023 (co-first; listed alphabetically)
Buljan, M., Banaei-Esfahani, A., Blattmann, P., Meier-Abt, F., Shao, W., Vitek, O., Tang, H., & Aebersold, R. (2023). A computational framework for the inference of protein complex remodeling from whole-proteome measurements. Nature Methods