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Updated: Jun 8, 2025

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
Functional Analysis of MS-Based Proteomics Data: From Protein Groups to Networks
Marie Locard-Paulet1, Nadezhda T Doncheva2, John H Morris3
1Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark; Institut de Pharmacologie et de Biologie Structurale (IPBS), Université de Toulouse, CNRS, Université Toulouse III-Paul Sabatier (UT3), Toulouse, France; Infrastructure nationale de protéomique, ProFI, FR 2048, Toulouse, France.
Abstract:
Mass spectrometry-based proteomics allows the quantification of thousands of proteins, protein variants, and their modifications, in many biological samples. These are derived from the measurement of peptide relative quantities, and it is not always possible to distinguish proteins with similar sequences due to the absence of protein-specific peptides. In such cases, peptide signals are reported in protein groups that can correspond to several genes. Here, we show that multi-gene protein groups have a limited impact on GO-term enrichment, but selecting only one gene per group affects network analysis. We thus present the Cytoscape app Proteo Visualizer (https://apps.cytoscape.org/apps/ProteoVisualizer) that is designed for retrieving protein interaction networks from STRING using protein groups as input and thus allows visualization and network analysis of bottom-up MS-based proteomics data sets.
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