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Related Concept Videos

Proteomics01:33

Proteomics

9.3K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
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Protein Networks02:26

Protein Networks

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Protein Networks02:26

Protein Networks

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
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Ribosome Profiling02:24

Ribosome Profiling

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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
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Quantitative Analysis01:12

Quantitative Analysis

1.3K
Quantitative analysis is a technique for measuring the amount of specific constituents in a sample. When the sample's composition is unknown, qualitative analysis is performed first to identify its components, which ensures that the correct substances are measured during the quantitative phase.
In quantitative analysis, two key measurements are made: the sample quantity and a property proportional to the amount of the analyte (the substance being analyzed). This forms the basis of the...
1.3K
High-Resolution Mass Spectrometry (HRMS)01:15

High-Resolution Mass Spectrometry (HRMS)

2.3K
The resolution of a mass spectrometer depends on the efficiency of separating ions with different ion masses. The mass of an atom is approximated to the sum of the masses of protons and neutrons inside, considering the masses of protons and neutrons as equal. However, the masses of the proton (1.6726 × 10−24 g) and neutron (1.6749 × 10−24 g) are not truly equal. There is a minor error in the expression of atomic masses relative to the simplest atom of hydrogen. For...
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Related Experiment Video

Updated: Jan 14, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

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JUMPshiny: A User-Friendly Platform for Comprehensive Analysis and Visualization of Quantitative Proteomics Data.

Aijun Zhang1,2, Yingxue Fu3, Zuo-Fei Yuan3

  • 1Department of Neurology, University of Tennessee Health Science Center, Memphis, Tennessee, USA.

Proteomics
|October 22, 2025
PubMed
Summary

JUMPshiny is a new R-Shiny web service for analyzing quantitative proteomics data. It offers interactive visualizations and a streamlined workflow for robust data processing and discovery in biological research.

Keywords:
JUMPshinyR packagesbioinformatics toolsdata analysisdata visualizationmass spectrometryquantitative proteomicssoftwareweb application

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Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
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Area of Science:

  • Proteomics
  • Bioinformatics
  • Computational Biology

Background:

  • Quantitative proteomics is crucial for understanding biological processes and disease mechanisms.
  • Analyzing and visualizing complex proteomics data requires advanced, user-friendly tools.

Purpose of the Study:

  • Introduce JUMPshiny, a novel R-Shiny web service for quantitative proteomics data analysis.
  • Provide a comprehensive platform for streamlined data processing, visualization, and statistical analysis.

Main Methods:

  • Developed JUMPshiny as an interactive web service using the R-Shiny framework.
  • Integrated established R libraries for robust computational analysis.
  • Included features for experimental design, data exploration, normalization, differential, and enrichment analyses.

Main Results:

  • Demonstrated automated quality control and interactive data visualization capabilities.
  • Showcased customizable statistical analyses for proteomics datasets.
  • Ensured computational robustness and reproducibility through integrated packages.

Conclusions:

  • JUMPshiny offers a powerful and accessible platform for the research community to analyze quantitative proteomics data.
  • The web service facilitates deeper insights into biological processes and disease mechanisms through enhanced data analysis.