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,...
Cluster Sampling Method01:20

Cluster Sampling Method

Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...

You might also read

Related Articles

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

Sort by
Same author

SeedMatExplorer: the transcriptome atlas of Arabidopsis seed maturation.

BMC plant biology·2026
Same author

Sequencing DNA methylation and hydroxymethylation at co-occurring chromatin features.

Nature communications·2026
Same author

Translational landscape during seed germination revealed by ribosome profiling.

The Plant journal : for cell and molecular biology·2026
Same author

Commentary on 'Untargeted CUT&Tag reads are enriched at accessible chromatin and restrict identification of potential G4-forming sequences in G4-targeted CUT&Tag experiments'.

Nucleic acids research·2025
Same author

ProkBERT PhaStyle: accurate phage lifestyle prediction with pretrained genomic language models.

Bioinformatics advances·2025
Same author

Rational design of induced regeneration via somatic embryogenesis in the absence of exogenous phytohormones.

The Plant cell·2025
Same journal

Biomedical Concept Recognition with Error-aware Negative-enhanced Ranking Framework.

Bioinformatics (Oxford, England)·2026
Same journal

TEDLH: Domain HMMs for sensitive detection of remote homologues.

Bioinformatics (Oxford, England)·2026
Same journal

PLNFGL: Joint Estimation of Multi-Condition Gene Networks from Single-cell RNA-seq Data.

Bioinformatics (Oxford, England)·2026
Same journal

MCFST: Spatial domain identification method based on multi-view graph convolutional network and graph fusion network.

Bioinformatics (Oxford, England)·2026
Same journal

SpaBiT: Enhancing Spatial Transcriptomics Resolution via Bidirectional Attention Transformers.

Bioinformatics (Oxford, England)·2026
Same journal

EDEL: Enhancing Dense Retrievers for Curation of Biomedical Knowledge Bases.

Bioinformatics (Oxford, England)·2026
See all related articles

Related Experiment Video

Updated: Jun 10, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Multi-netclust: an efficient tool for finding connected clusters in multi-parametric networks.

Arnold Kuzniar1, Somdutta Dhir, Harm Nijveen

  • 1Laboratory of Bioinformatics, Wageningen University and Research Centre, PO Box 569, 6700 AN Wageningen, The Netherlands.

Bioinformatics (Oxford, England)
|August 4, 2010
PubMed
Summary
This summary is machine-generated.

Multi-netclust is a new tool for analyzing network data. It efficiently finds connected clusters across multiple networks using a graph algorithm, aiding biological data analysis.

More Related Videos

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

Related Experiment Videos

Last Updated: Jun 10, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

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

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Network Analysis

Background:

  • Analyzing complex biological networks requires specialized tools.
  • Existing methods may lack efficiency or flexibility for multi-network data.

Purpose of the Study:

  • To introduce Multi-netclust, a novel tool for extracting connected clusters from multiple networks.
  • To provide a memory-efficient and fast algorithm for network cluster analysis.

Main Methods:

  • Utilizes user-defined thresholds to combine network matrices.
  • Employs a straightforward, memory-efficient graph algorithm.
  • Implemented in C/C++ for performance.

Main Results:

  • Successfully extracts connected clusters present in all or either networks.
  • Demonstrates high performance, processing large networks (>10^6 nodes, 10^8 edges) in minutes.
  • Offers both form-based and command-line interfaces for Linux.

Conclusions:

  • Multi-netclust is an efficient and versatile tool for multi-network cluster analysis.
  • Its speed and memory efficiency make it suitable for large-scale biological network data.
  • Facilitates the discovery of biologically relevant patterns across integrated networks.