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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 8, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

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

Published on: October 19, 2021

Exact parallel maximum clique algorithm for general and protein graphs.

Matjaž Depolli1, Janez Konc, Kati Rozman

  • 1Jožef Stefan Institute , Jamova 39, SI-1000 Ljubljana, Slovenia.

Journal of Chemical Information and Modeling
|August 23, 2013
PubMed
Summary
This summary is machine-generated.

A new parallel maximum clique algorithm, MaxCliquePara, efficiently finds the largest fully connected subgraph in complex graphs. This algorithm significantly speeds up computations on both benchmark and protein-derived datasets.

Related Experiment Videos

Last Updated: May 8, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

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

Published on: October 19, 2021

Area of Science:

  • Computer Science
  • Graph Theory
  • Bioinformatics

Background:

  • The maximum clique problem is computationally challenging, with applications in various fields.
  • Existing sequential algorithms have limitations in handling large-scale graph data.

Purpose of the Study:

  • To develop an efficient exact parallel algorithm for finding the maximum clique.
  • To improve upon the performance of state-of-the-art sequential maximum clique algorithms.

Main Methods:

  • Implementation of a novel sequential branch and bound algorithm (MaxCliqueSeq).
  • Parallelization of MaxCliqueSeq by distributing the search tree across multiple cores (MaxCliquePara).
  • Evaluation on DIMACS benchmark graphs and protein-derived product graphs.

Main Results:

  • MaxCliqueSeq outperforms existing sequential algorithms on benchmark and protein graphs.
  • MaxCliquePara achieves significant speedups, up to 2 orders of magnitude on large DIMACS graphs.
  • Parallelization effectively utilizes multi-core architectures for enhanced performance.

Conclusions:

  • The MaxCliquePara algorithm offers a substantial performance improvement for maximum clique detection.
  • The parallel approach is highly effective for large and complex graph structures.
  • The developed algorithms are publicly available for research use.