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Updated: May 23, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
Mass spectrometry-based proteomics and network biology.
Ariel Bensimon1, Albert J R Heck, Ruedi Aebersold
1Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, CH 8093, Switzerland. bensimon@imsb.biol.ethz.ch
Systems biology uses mass spectrometry (MS)-based proteomics to map molecular interaction networks. This approach reveals how network changes drive cellular phenotypes, advancing our understanding of life sciences.
Area of Science:
- Life Sciences
- Molecular Biology
- Systems Biology
Background:
- A paradigm shift in life sciences emphasizes molecular interaction networks between genotype and phenotype.
- These networks, central to systems biology, network biology, and integrative biology, dynamically influence observable phenotypes.
- Mass spectrometry (MS)-based proteomics is a key technology for analyzing proteomes.
Purpose of the Study:
- To review the application of MS-based proteomics in network biology.
- To highlight how proteomics identifies network components and dynamics.
- To discuss the correlation between network rewiring and cellular phenotypes.
Main Methods:
- Utilizing mass spectrometry (MS)-based proteomics for protein identification and quantification.
- Applying proteomics to map nodes and edges within biological networks.
- Analyzing perturbation-induced changes in molecular networks.
Main Results:
- MS-based proteomics has been instrumental in identifying components of biological networks.
- Proteomics enables the quantification of dynamic network changes in response to perturbations.
- The approach links network rewiring events to specific cellular phenotypes.
Conclusions:
- MS-based proteomics is a powerful tool for dissecting biological networks.
- This technology facilitates the understanding of genotype-phenotype relationships through network analysis.
- Future directions involve further integration of MS-based proteomics within the network biology paradigm.
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