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

Cluster Sampling Method01:20

Cluster Sampling Method

11.6K
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...
11.6K
Vesicular Tubular Clusters01:45

Vesicular Tubular Clusters

2.4K
After budding out from the ER membrane, some COPII vesicles lose their coat and fuse with one another to form larger vesicles and interconnected tubules called vesicular tubular clusters or VTCs. These clusters constitute a compartment at the ER-Golgi interface known as ERGIC (Endoplasmic Reticulum Golgi Intermediate Compartment). The ERGIC is a mobile membrane-bound cargo transport system that sorts proteins secreted from ER and delivers them to the Golgi.
With the help of motor proteins such...
2.4K
RNA-seq03:21

RNA-seq

9.8K
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
9.8K
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

18.8K
The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
18.8K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

5.7K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
5.7K

You might also read

Related Articles

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

Sort by
Same author

Characterization of the immune landscape in healthy mouse prostate and during prostate cancer progression.

Oncoimmunology·2025
Same author

SciGeneX: enhancing transcriptional analysis through gene module detection in single-cell and spatial transcriptomics data.

NAR genomics and bioinformatics·2025
Same author

mimicINT: A workflow for microbe-host protein interaction inference.

F1000Research·2025
Same author

Type III interferons induce pyroptosis in gut epithelial cells and impair mucosal repair.

Cell·2024
Same author

Lymphotoxin limits Foxp3<sup>+</sup> regulatory T cell development from Foxp3<sup>lo</sup> precursors via IL-4 signaling.

Nature communications·2024
Same author

Characterizing intergenic transcription at RNA polymerase II binding sites in normal and cancer tissues.

Cell genomics·2023
Same journal

Emotional intelligence: An important skill to learn now more than ever.

F1000Research·2026
Same journal

East Mediterranean Lineage of <i>Brucella melitensis</i> in Human Isolates and Milk Samples in Oman Using MLVA-14.

F1000Research·2026
Same journal

Application of K-Means Clustering for Job Applicant Analysis in Construction Firms Using R.

F1000Research·2026
Same journal

The influence of self-esteem and emotional intelligence on addiction to social networks in Peruvian university students.

F1000Research·2026
Same journal

A Bibliometric Analysis of Music's Role in Promoting Well-Being in Health Science Research.

F1000Research·2026
Same journal

Social Innovation in Entrepreneurship: A Strategic Pathway to Poverty Reduction for Sustainable Development: A systematic Literature Review.

F1000Research·2026
See all related articles

Related Experiment Video

Updated: Jun 8, 2025

Rapid High-throughput Species Identification of Botanical Material Using Direct Analysis in Real Time High Resolution Mass Spectrometry
11:14

Rapid High-throughput Species Identification of Botanical Material Using Direct Analysis in Real Time High Resolution Mass Spectrometry

Published on: October 2, 2016

11.5K

Clust&See3.0 : clustering, module exploration and annotation.

Fabrice Lopez1, Lionel Spinelli1,2, Christine Brun1,3

  • 1TAGC (UMR1090), Aix-Marseille Université, INSERM, Turing Centre for Living Systems, Marseille, 13009, France.

F1000Research
|November 4, 2024
PubMed
Summary
This summary is machine-generated.

Clust&See3.0 enhances Cytoscape for analyzing large biological networks. This tool aids in identifying, visualizing, and annotating network clusters and modules, crucial for multi-omics data interpretation.

Keywords:
cluster annotationsclusteringfunctional modulesgraph partitioninginteraction networksstatistical enrichment.visualization

More Related Videos

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
05:12

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

11.4K
An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

3.3K

Related Experiment Videos

Last Updated: Jun 8, 2025

Rapid High-throughput Species Identification of Botanical Material Using Direct Analysis in Real Time High Resolution Mass Spectrometry
11:14

Rapid High-throughput Species Identification of Botanical Material Using Direct Analysis in Real Time High Resolution Mass Spectrometry

Published on: October 2, 2016

11.5K
ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
05:12

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

11.4K
An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

3.3K

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Cytoscape is a widely used open-source platform for network visualization and analysis.
  • Analyzing large-scale biological networks, such as protein-protein interaction networks, presents significant challenges in holistic interpretation.

Purpose of the Study:

  • To introduce Clust&See3.0, an advanced Cytoscape application designed for comprehensive network cluster and module analysis.
  • To provide enhanced functionalities for custom node annotation and statistical enrichment analysis within biological networks.

Main Methods:

  • Development of Clust&See3.0 as a novel version of a Cytoscape app.
  • Integration of features for identifying, visualizing, and manipulating network clusters and modules.
  • Implementation of custom node annotation and statistical enrichment computation capabilities.

Main Results:

  • Clust&See3.0 offers enriched functionalities for detailed network cluster analysis.
  • The app facilitates a deeper understanding of biological module composition, particularly with growing multi-omics data.
  • A use case demonstrates the practical value of these functionalities.

Conclusions:

  • Clust&See3.0 provides a comprehensive toolkit for network cluster analysis.
  • The application supports the entire workflow from identification and visualization to annotation and statistical analysis.
  • Its features are valuable for interpreting complex biological networks and multi-omics datasets.