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 Experiment Videos

iVici: Interrelational Visualization and Correlation Interface.

Kirill Tarassov1, Stephen W Michnick

  • 1Département de Biochimie and Centre Robert-Cedergren, Bioinformatiques et Genomiques, Université de Montréal, CP 6128, Succursale Centre-ville, Montréal, Québec, H3C 3J7, Canada. kirill.tarassov@umontreal.ca

Genome Biology
|January 20, 2006
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

The scientific legacy of Martin Karplus from the perspective of his collaborators.

Biophysical journal·2026
Same author

Protein-protein interactions are a major source of epistasis in genetic interaction networks.

Nature communications·2026
Same author

Tetravalent antibodies are more potent and efficacious erythropoiesis-stimulating agents than erythropoietin in vivo.

Protein science : a publication of the Protein Society·2026
Same author

An asymmetric tetrabody is a potent and efficacious agonist of the erythropoietin receptor in vitro and in vivo.

Protein science : a publication of the Protein Society·2025
Same author

Three decades of protein-fragment complementation.

Nature reviews. Molecular cell biology·2024
Same author

Biomolecular condensates as drivers of membrane trafficking and remodelling.

Current opinion in cell biology·2024
Same journal

Somatic mobility of transposons is explosive and shaped by distinct integration biases in Arabidopsis thaliana.

Genome biology·2026
Same journal

UK Biobank whole-genome sequencing reveals robust contributions of rare variants to complex-trait heritability.

Genome biology·2026
Same journal

A one-week automated genome-wide optical pooled screen using OttoSeq.

Genome biology·2026
Same journal

Integrated lipidomic and transcriptomic profiling of the host response in human malaria.

Genome biology·2026
Same journal

Centromeric satellite expansion drives genome evolution in the snowy owl.

Genome biology·2026
Same journal

Mapping the landscape of allele-specific expression in porcine genomes.

Genome biology·2026
See all related articles

We created iVici, a new application for analyzing cellular networks. It allows simultaneous visualization and correlation of multiple gene, mRNA, or protein datasets for comprehensive network comparison.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Cellular networks are complex and involve interactions between genes, mRNAs, and proteins.
  • Analyzing these networks requires tools capable of handling multiple, diverse datasets simultaneously.
  • Existing methods may lack the integrated visualization and correlation capabilities needed for in-depth network analysis.

Purpose of the Study:

  • To develop a novel application, iVici, for the analysis of cellular networks.
  • To enable simultaneous visualization and correlation of multiple biological datasets.
  • To facilitate the comparison and investigation of network dynamics.

Main Methods:

  • Development of the iVici application.
  • Representation of cellular networks as addressable symmetric or asymmetric two-dimensional matrices.

Related Experiment Videos

  • Implementation of simultaneous visualization and correlation features for multiple datasets.
  • Integration of visual overlay and addressable gene annotation access.

    • Main Results:

    • iVici enables the analysis of cellular networks represented as matrices.
    • The application allows simultaneous visualization and correlation of diverse datasets (genes, mRNAs, proteins).
    • Users can compare different network types (e.g., protein-protein interactions, genetic networks) and study network reorganization.

    Conclusions:

    • iVici provides a powerful platform for analyzing and comparing complex cellular networks.
    • The tool facilitates a deeper understanding of biological network structures and dynamics.
    • iVici supports the integrated analysis of multi-omics data for systems biology research.