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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics.
David Vanderwall1, Poudel Suresh2, Yingxue Fu3
1Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital.
Journal of Visualized Experiments : Jove
|November 8, 2021
Summary
JUMPn software aids biological insight discovery from large proteomic datasets. It organizes proteomes into co-expression clusters and protein-protein interaction networks for easier analysis.
Area of Science:
- Proteomics
- Systems Biology
- Bioinformatics
Background:
- Mass spectrometry advances enable deep proteome profiling.
- Analyzing large proteomic datasets for biological insights remains challenging.
Purpose of the Study:
- Introduce JUMPn software and protocol for systems biology analysis of proteomic data.
- Facilitate organization of proteomes into co-expression clusters and protein-protein interaction networks.
Main Methods:
- Developed JUMPn software using R/Shiny platform.
- Protocol involves software installation, defining differentially expressed proteins, clustering, and network analysis.
- Integrated data visualization and user-friendly interface.
Main Results:
- JUMPn streamlines co-expression clustering, pathway enrichment, and protein-protein interaction module detection.
- Provides integrated data visualization for user-friendly interpretation.
- Applicable to various quantitative proteomic datasets, including isobaric labeling and label-free.
Conclusions:
- JUMPn offers a powerful tool for biological interpretation of quantitative proteomics data.
- Facilitates the organization and analysis of complex proteomic datasets.
- Enhances the derivation of biological insights from deep proteome profiling.
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