Functional Analysis of MS-Based Proteomics Data: From Protein Groups to Networks

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.

Authors

Institutions

Publication Details

Journal
Molecular & Cellular Proteomics
Published
2024-10-31
DOI
https://doi.org/10.1016/j.mcpro.2024.100871
Citations
7
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
1.64

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Functional Analysis of MS-Based Proteomics Data: From Protein Groups to Networks

Lars Juhl Jensen, Marie Locard‐Paulet, John H. Morris, Nadezhda T. Doncheva
7 citations
Molecular & Cellular Proteomics
Bioinformatics and Genomic Networks
1.64
article

Functional Analysis of MS-Based Proteomics Data: From Protein Groups to Networks

Lars Juhl Jensen, Marie Locard‐Paulet, John H. Morris, Nadezhda T. Doncheva
article en
7 citations

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.

Molecular & Cellular ProteomicsVol. 23(12)
University of Copenhagen (DK), Centre National de la Recherche Scientifique (FR), Université Toulouse III - Paul Sabatier (FR), University of California, San Francisco (US), Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR), Novo Nordisk Foundation (DK), Institut de Recherche Interdisciplinaire de Grenoble (FR), Institut de Pharmacologie et de Biologie Structurale (FR), Biocom (US)
Agence Nationale de la Recherche, Novo Nordisk, Ministère de l'Enseignement Supérieur et de la Recherche, Novo Nordisk Fonden, National Human Genome Research Institute, National Institute of General Medical Sciences
Zero hunger
Openalex Percentile: Top 16%
Bioinformatics and Genomic Networks
1.64
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.