ProteomicsDB (https://www.ProteomicsDB.org) started as a protein-centric in-memory database for the exploration of large collections of quantitative mass spectrometry-based proteomics data. The data types and contents grew over time to include RNA-Seq expression data, drug-target interactions and…
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Prosit (https://www.proteomicsdb.org/prosit/) is a deep learning framework that offers free and easy generation of custom in-silico spectral libraries using very high quality predicted HCD MS2 spectra for any organism and protease as well as iRT prediction.
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We describe and evaluate a robust and cost-effective protocol for TMT labeling that reduces the quantity of required labeling reagent by a factor of eight and achieves complete labeling.
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We are very happy to announce that Jana Zecha has been awarded the MCP early-career award by Molecular & Cellular Proteomics and is recognized as a rising star in proteomics. Congratulations!
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We are very excited to announce that Bernhard Küster and the lab have been awarded an ERC advanced grant for "Exploiting the Tumor Proteome Activity Status for Future Cancer Therapies".
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We congratulate Dr. Stephanie Heinzlmeir for being awarded with promotion prize of the German Society for Proteome Research (Deutsche Gesellschaft für Proteomforschung) for her outstanding dissertation.
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Chemical proteomic approaches utilizing immobilized, broad-selective kinase inhibitors (Kinobeads) have proven valuable for the elucidation of a compound’s target profile often revealing potentially synergistic or toxic off-targets. Here, we report the development of a novel version of Kinobeads…
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