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Related Concept Videos

Protein Networks02:26

Protein Networks

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,...
Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
Proteomics01:33

Proteomics

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 proteomics...

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Related Experiment Video

Updated: Jun 20, 2026

Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling
09:35

Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling

Published on: April 1, 2017

Network-assisted protein identification and data interpretation in shotgun proteomics.

Jing Li1, Lisa J Zimmerman, Byung-Hoon Park

  • 1Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37232-8340, USA.

Molecular Systems Biology
|August 20, 2009
PubMed
Summary

This study introduces a clique-enrichment approach (CEA) to improve shotgun proteomics by rescuing eliminated proteins using protein interaction networks. CEA enhances protein identification and reveals disease-related protein modules, advancing biological interpretation.

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Last Updated: Jun 20, 2026

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Area of Science:

  • Proteomics
  • Bioinformatics
  • Systems Biology

Background:

  • Shotgun proteomics data analysis relies on protein assembly and biological interpretation.
  • Current pipelines often eliminate potentially important proteins by treating them independently.
  • Biological functions frequently emerge from protein interactions, not isolated proteins.

Purpose of the Study:

  • To develop a novel approach for rescuing eliminated proteins in proteomics.
  • To leverage protein interaction networks for improved protein identification and biological insights.
  • To enhance the biological interpretation of shotgun proteomics data.

Main Methods:

  • Developed a clique-enrichment approach (CEA) integrating protein interaction networks.
  • Applied CEA to multiple proteomics datasets to identify and rescue proteins.
  • Validated rescued proteins using literature and transcriptome data.
  • Analyzed protein networks to identify modular organization.

Main Results:

  • CEA increased protein identification by 8-23% across tested datasets with 85% accuracy.
  • Rescued proteins showed significant support from literature and transcriptome data.
  • Application to breast cancer data identified known cancer-related genes.
  • CEA revealed modular protein organization relevant to disease mechanisms.

Conclusions:

  • The clique-enrichment approach (CEA) effectively rescues eliminated proteins in shotgun proteomics.
  • CEA enhances protein identification accuracy and biological relevance.
  • Network-based analysis with CEA provides deeper insights into molecular mechanisms and disease associations.