ccNetViz: a WebGL-based JavaScript library for visualization of large networks
Author(s) -
Aleš Saska,
David Tichy,
Robert Moore,
Achilles Rasquinha,
Caner Akdas,
Xiaodong Zhao,
Renato Fabbri,
Ana Jeličić,
Gaurav Grover,
Himanshu Jotwani,
Mohamed Shadab,
Resa Helikar,
Tomáš Helikar
Publication year - 2020
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btaa559
Subject(s) - computer science , javascript , visualization , documentation , node (physics) , world wide web , personalization , open source , enhanced data rates for gsm evolution , information retrieval , data mining , software , programming language , artificial intelligence , structural engineering , engineering
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.
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