Jove
Visualize
Contact Us

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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Evaluating microbial network inference methods: moving beyond synthetic data with reproducibility-driven benchmarks.

BMC bioinformatics·2026
Same author

Rethinking bioinformatics expertise in the era of artificial intelligence.

NPJ digital medicine·2026
Same author

Enhancing protein structure prediction: evaluating the role of amino acid physicochemical features in homology search.

Briefings in bioinformatics·2026
Same author

Protrec2: tissue-specific network-based missing protein recovery method.

Briefings in bioinformatics·2025
Same author

Establishing the Asia & Pacific Bioinformatics Joint Congress: a historic milestone in regional bioinformatics collaboration.

Briefings in bioinformatics·2025
Same author

Comprehensive benchmarking of methods for mutation calling in circulating tumor DNA.

Nature communications·2025
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Jun 8, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Protein complex prediction based on k-connected subgraphs in protein interaction network.

Mahnaz Habibi1, Changiz Eslahchi, Limsoon Wong

  • 1Faculty of Mathematics, Shahid-Beheshti University, gc, Tehran, Iran.

BMC Systems Biology
|September 18, 2010
PubMed
Summary

A new protein complex prediction method, CFA, uses subgraph connectivity to identify protein complexes in interaction networks. CFA improves accuracy compared to existing methods, aiding cellular mechanism research.

More Related Videos

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

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

Related Experiment Videos

Last Updated: Jun 8, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

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

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

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Protein complexes are crucial for cellular functions.
  • Existing protein complex prediction methods often assume dense subgraphs, which may not reflect real-world data.
  • Protein interaction data is often incomplete, posing challenges for accurate complex prediction.

Purpose of the Study:

  • To propose a novel protein complex prediction method, CFA (Connectivity-based Functional Association).
  • To evaluate CFA's performance against established methods using benchmark datasets.
  • To address limitations of existing methods by considering varied subgraph connectivity.

Main Methods:

  • Developed the CFA method based on connectivity number within subgraphs.
  • Utilized two benchmark datasets, MIPS and Aloy, containing 1142 and 61 known protein complexes, respectively.
  • Compared CFA with CMC, MCL, PCP, and RNSC using recall and precision metrics.

Main Results:

  • CFA demonstrates improved accuracy in predicting protein complexes.
  • The method shows competitive precision while identifying more correct complexes.
  • Performance was evaluated across multiple protein interaction networks.

Conclusions:

  • Connectivity number is an effective basis for predicting diverse protein complexes.
  • The CFA method offers a more robust approach to protein complex prediction.
  • The CFA program and associated results are publicly available for research use.