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Related Concept Videos

Protein Networks02:26

Protein Networks

4.7K
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,...
4.7K
Protein Networks02:26

Protein Networks

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Protein-protein Interfaces02:04

Protein-protein Interfaces

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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
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Updated: Mar 22, 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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Network-Based Protein Biomarker Discovery Platforms.

Minhyung Kim1, Daehee Hwang1

  • 1Department of New Biology and Center for Plant Aging Research, Institute for Basic Science, Daegu Gyeongbuk Institute of Science and Technology, Daegu 42988, Korea.

Genomics & Informatics
|April 23, 2016
PubMed
Summary
This summary is machine-generated.

Mass spectrometry proteomics identifies differentially expressed proteins (DEPs) in diseases. Network analysis of DEPs reveals disease-related pathways and key protein biomarkers for improved disease state indicators.

Keywords:
LC-MS/MSbiomarkersnetwork analysisproteomics

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Area of Science:

  • Biochemistry
  • Proteomics
  • Systems Biology

Background:

  • Mass spectrometry-based proteomics generates global proteome data from human disease samples.
  • Comparative analysis identifies differentially expressed proteins (DEPs) in disease versus control samples.
  • Protein biomarkers are selected as key molecules indicating disease states.

Purpose of the Study:

  • To review analytical platforms for network-based protein biomarker discovery.
  • To highlight key components within these platforms.
  • To emphasize the utility of cellular pathways and network analysis for disease indication.

Main Methods:

  • Review of network-based approaches for identifying disease-related pathways.
  • Analysis of methodologies for selecting key molecules representing altered cellular pathways.
  • Summarization of analytical platforms for protein biomarker discovery.

Main Results:

  • Differential abundance of proteins (DEPs) can be identified using comparative proteomic analysis.
  • Network analysis of DEPs effectively identifies altered cellular pathways in disease.
  • Cellular pathways offer superior disease state indications compared to individual molecules.

Conclusions:

  • Network-based approaches enhance the identification of disease-related pathways and key protein biomarkers.
  • Proteomic data analysis, particularly network analysis, is crucial for biomarker discovery.
  • Understanding altered cellular pathways is vital for accurate disease state assessment.