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New pattern recognition method enables easier identification of the cells that cause disease

The research group of Prof. Ria Baumgrass at the DRFZ has developed a new strategy for pattern recognition for the analysis and visualisation of high-dimensional cytometric data, and published it in the journal Frontiers in Immunology. This “pattern recognition of immune cells” (PRI) approach has now been used to extract new information from already published datasets. In this way, it was possible to identify immune cells that were activated during the course of cancer therapy, i.e. the ones that were probably involved in the success of the therapy. The new method can now also be used to identify the immune cells in rheumatic diseases that might cause or attenuate the disease.

Link to publication
Hoang Y, Gryzik S, Hoppe I, Rybak A, Schädlich M, Kadner I, Walther D, Vera J, Radbruch A, Groth D, Baumgart S, Baumgrass R. PRI: Re-Analysis of a Public Mass Cytometry Dataset Reveals Patterns of Effective Tumor Treatments. Front Immunol. 2022 May 3;13:849329. doi: 10.3389/fimmu.2022.849329. PMID: 35592315; PMCID: PMC9110672.
Update: Latest publication about utilizing bin-based pattern recognition by September 2022
Mohr E, Hinnenthal T, Gryzik S, Hoang Y, Lischke T, Retzlaff J, Mekonnen A, Paul F, Valleriani A, Radbruch A, Vera J, Baumgrass R. Bin-based visualization of cytokine-co-expression patterns of IL-10-producing CD4 T cell subsets. Eur J Immunol. 2022 Sep 6. doi: 10.1002/eji.202249829. Epub ahead of print. PMID: 36067024.
Signal Transduction apl. Prof. Dr. Ria Baumgrass Phone +49 (0)30 28460-732/699 baumgrass@drfz.de more
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