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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,...
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,...
Protein-protein Interfaces02:04

Protein-protein Interfaces

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 polypeptide...
Protein-Protein Interfaces02:04

Protein-Protein Interfaces

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 polypeptide...
Protein Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order to...
Protein Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order to...

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Related Experiment Video

Updated: May 7, 2026

Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry
14:58

Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry

Published on: November 12, 2012

Clustering based on multiple biological information: approach for predicting protein complexes.

Xiwei Tang, Qilong Feng, Jianxin Wang

    IET Systems Biology
    |September 27, 2013
    PubMed
    Summary
    This summary is machine-generated.

    A new method, CMBI, enhances protein complex prediction by integrating gene expression, essential protein data, and protein-protein interaction (PPI) data. This approach significantly improves accuracy compared to existing computational techniques.

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    Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry
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    Published on: November 12, 2012

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    Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay (PCA) in Living Cells
    08:38

    Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay (PCA) in Living Cells

    Published on: March 3, 2015

    Area of Science:

    • Computational Biology
    • Systems Biology
    • Bioinformatics

    Background:

    • Protein complexes are crucial for biological functions.
    • Existing computational methods for protein complex prediction are limited by insufficient protein-protein interaction (PPI) data.
    • Accurate identification of protein complexes is vital for understanding cellular mechanisms.

    Purpose of the Study:

    • To develop a novel computational method, Clustering based on Multiple Biological Information (CMBI), for discovering protein complexes.
    • To improve the accuracy of protein complex prediction by integrating diverse biological data sources.
    • To overcome the limitations of relying solely on PPI data.

    Main Methods:

    • Integrated gene expression profiles, essential protein information, and PPI data.
    • Defined functional similarity using edge-clustering and Pearson correlation coefficients.
    • Utilized essential proteins as seeds for complex construction and employed a redundancy-filtering procedure.
    • Expanded complexes using additional proteins and investigated parameter effects (T and R).

    Main Results:

    • CMBI demonstrated superior performance in discovering protein complexes compared to state-of-the-art methods.
    • Analysis using GO::TermFinder confirmed the enhanced accuracy and biological relevance of CMBI-predicted complexes.
    • Matching analyses against reference complexes validated the effectiveness of the CMBI approach.

    Conclusions:

    • CMBI offers a significant advancement in computational protein complex prediction.
    • The integration of multiple biological information sources enhances the reliability and accuracy of complex identification.
    • CMBI provides a robust framework for exploring protein complex organization in biological systems.