Jove
Visualize
Contact Us
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 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,...

You might also read

Related Articles

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

Sort by
Same author

Development and Psychometric Validation of the Career Identity Questionnaire for Vocational School Students.

Behavioral sciences (Basel, Switzerland)·2026
Same author

Biodegradable cross-linked flavone networks featuring either ester or carbamate linkages for controlled delivery of anti-cancer agents.

RSC advances·2026
Same author

Combining graphlets and random walks for capturing complex network topology.

Scientific reports·2026
Same author

Low-molecular weight organogel matrices as crystallisation media for active pharmaceutical ingredients.

Journal of materials chemistry. B·2026
Same author

Polymerisation processes and computational methods to control structure: general discussion.

Faraday discussions·2025
Same author

MONFIT: multi-omics factorization-based integration of time-series data sheds light on Parkinson's disease.

NAR molecular medicine·2025
Same journal

OpenIMC: an open-source platform for analyzing single-cell and spatial proteomics by imaging mass cytometry.

BMC bioinformatics·2026
Same journal

NAP: an open source pipeline for cross-domain microbiome profiling using Nanopore sequencing-derived amplicon data.

BMC bioinformatics·2026
Same journal

SurvGME: an R package for survival analysis with graphical and measurement error models.

BMC bioinformatics·2026
Same journal

SimMapNet: a Bayesian framework for gene regulatory network inference using gene ontology similarities as external hint.

BMC bioinformatics·2026
Same journal

Dual channel drug-drug interactions extraction based on cross attention.

BMC bioinformatics·2026
Same journal

FeSseqdb: a curated sequence-level database and interpretable machine learning framework for identifying iron-sulfur proteins.

BMC bioinformatics·2026
See all related articles

Related Experiment Video

Updated: Jun 5, 2026

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data
07:11

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data

Published on: November 10, 2023

GraphCrunch 2: Software tool for network modeling, alignment and clustering.

Oleksii Kuchaiev1, Aleksandar Stevanović, Wayne Hayes

  • 1Department of Computer Science, University of California, Irvine, CA, USA.

BMC Bioinformatics
|January 20, 2011
PubMed
Summary
This summary is machine-generated.

GraphCrunch 2 is a new software tool for analyzing biological networks. It offers advanced network alignment and clustering to reveal functional similarities between proteins, improving our understanding of cellular processes.

More Related Videos

Introductory Analysis and Validation of CUT&RUN Sequencing Data
04:58

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

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

Related Experiment Videos

Last Updated: Jun 5, 2026

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data
07:11

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data

Published on: November 10, 2023

Introductory Analysis and Validation of CUT&RUN Sequencing Data
04:58

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

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:

  • Computational Biology
  • Bioinformatics
  • Systems Biology

Background:

  • Experimental biotechnology generates vast amounts of protein-protein interaction (PPI) data.
  • Network topology is crucial for understanding PPI network function.
  • Computational methods are needed for modeling, comparing, and aligning biological networks.

Purpose of the Study:

  • To introduce GraphCrunch 2, a software tool for analyzing biological networks.
  • To provide tools for network modeling, comparison, alignment, and clustering.
  • To facilitate the discovery of functional relationships within PPI networks.

Main Methods:

  • GraphCrunch 2 implements popular random network models for comparison with data networks.
  • The GRAph ALigner (GRAAL) algorithm performs topological network alignment.
  • An algorithm for topology-based node clustering within networks is included.

Main Results:

  • GraphCrunch 2 compares data networks against various network models using network properties.
  • GRAAL identifies extensive regions of topological and functional similarity between networks.
  • Topology-based clustering reveals functional similarities between proteins in yeast and human PPI networks, suggesting distinct graph model families for eukaryotic and viral PPI networks.

Conclusions:

  • GraphCrunch 2 is an open-source software tool for advanced biological network analysis.
  • It leverages parallel processing for computationally intensive tasks on multi-core CPUs.
  • The tool is available for Windows and Linux platforms for research use.