ccNetViz: A WebGL-based JavaScript library for visualization of large networks

Ales Saska, David Tichy, Robert Moore, Achilles Rasquinha, Caner Akdas, Xiaodong Zhao, Renato Fabbri, Ana Jeličić, Gaurav Grover, Himanshu Jotwani, Mohamed Shadab, Resa M. Helikar, Tomáš Helikar

Research output: Contribution to journalArticlepeer-review

Abstract

Summary: Visualizing a network provides a concise and practical understanding of the information it represents. Open-source web-based libraries help accelerate the creation of biologically based networks and their use. ccNetViz is an open-source, high speed and lightweight JavaScript library for visualization of large and complex networks. It implements customization and analytical features for easy network interpretation. These features include edge and node animations, which illustrate the flow of information through a network as well as node statistics. Properties can be defined a priori or dynamically imported from models and simulations. ccNetViz is thus a network visualization library particularly suited for systems biology. Availability and implementation: The ccNetViz library, demos and documentation are freely available at http://helikarlab.github.io/ccNetViz/. Supplementary information: Supplementary data are available at Bioinformatics online.

Original languageEnglish (US)
Pages (from-to)4527-4529
Number of pages3
JournalBioinformatics
Volume36
Issue number16
DOIs
StatePublished - Aug 15 2020

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

Fingerprint

Dive into the research topics of 'ccNetViz: A WebGL-based JavaScript library for visualization of large networks'. Together they form a unique fingerprint.

Cite this