Matthias Mann
Research Department Proteomics and Signal Transduction
Mass Spectrometry, Systems Biology, Bioinformatics, Signal Transduction, Posttranslational modifications, Metabolic diseases, Clinical proteomics, Cancer
The department of Proteomics and Signal Transduction is headed by Prof. Matthias Mann and was established in 2005. Matthias Mann is the highest cited German researcher by his h-index of more than 287 and over 400,000 citations ( google scholar). The Mann lab is a leader in the technology and application of mass spectrometry-based proteomics and has been at the forefront of the field for almost three decades. The core research interests of the group are signal transduction, biomarker discovery and metabolic diseases. Another focus is the development of mass spectrometric and proteomic methods for application in biological and clinical contexts. The group also develops computer algorithms for automated identification and quantification of peptides as well as systems biological and clinical knowledge mining. Ultimately, our vision is to transfer proteomics knowledge into clinics for predictive, diagnostic and preventive purposes. We are a highly collaborative team and involved in several networks including Bill & Melinda Gates Foundation, Chan Zuckerberg Initiative and Aligning Science Across Parkinson's (ASAP) in partnership with The Michael J. Fox Foundation for Parkinson’s Research (MJFF).
Research Highlights/ Reviews/ Perspectives
Mass-spectrometry-based proteomics: from single cells to clinical applications.
Guo T, Steen JA, Mann M.Nature. 2025 Feb;638(8052):901-911. doi: 10.1038/s41586-025-08584-0. Epub 2025 Feb 26.PMID: 40011722 Review.
A new understanding of tissue biology from MS-based proteomics at single-cell resolution.
Nordmann TM, Mund A, Mann M.Nat Methods. 2024 Dec;21(12):2220-2222. doi: 10.1038/s41592-024-02541-x.
Deep Visual Proteomics defines single-cell identity and heterogeneity
Spatial single-cell mass spectrometry defines zonation of the hepatocyte proteome
Artificial intelligence for proteomics and biomarker discovery
Data-independent acquisition method for ubiquitinome analysis reveals regulation of circadian biology
Spatial proteomics identifies JAKi as treatment for a lethal skin disease