Analysis and Visualization of Dynamic Networks Using the DyNet App for Cytoscape. Issue 1 (31st August 2018)

• Record Type: Journal Article
• Authors: Salamon, John; Goenawan, Ivan H.; Lynn, David J.
• Editors: Baxevanis, Andreas D.; Petsko, Gregory A.; Stein, Lincoln D.; Stormo, Gary D.
• Is Part Of: Current protocols in bioinformatics. Volume 63:Issue 1(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-08-31
• Subjects: Cytoscape 3 -- dynamic network -- DyNet -- network analysis; Bioinformatics -- Laboratory manuals; Nucleotide sequence -- Laboratory manuals; Amino acid sequence -- Laboratory manuals; Base Sequence; Amino Acid Sequence; Computational Biology -- methods; Databases, Genetic; Proteins -- analysis; Sequence Analysis -- methods; Sequence Homology; Amino acid sequence; Bioinformatics; Nucleotide sequence; Laboratory Manuals; Laboratory manuals; 570.285
• DOI: 10.1002/cpbi.55
• Languages: English
• ISSNs: 1934-3396

Abstract

Abstract: Biological processes are regulated at a cellular level by tightly controlled molecular interaction networks, which are collectively known as the interactome. The interactome is not a static entity, but instead is dynamically reorganized or "rewired" under varying temporal, spatial, and environmental conditions. Most network analysis and visualization tools have, to date, been developed for static representations of molecular interaction data. Here, we describe a protocol that provides a step‐by‐step guide to DyNet, a Cytoscape 3 application that facilitates the visualization and analysis of dynamic molecular interaction networks. DyNet represents a dynamic network as a set of state graphs that are synchronized in their layout. This synchronization is managed in real time and is automatically updated when a graph is manipulated by a user (e.g., dragging, zooming, moving a node). DyNet also provides several statistical tools enabling users to quickly identify and analyze the most 'rewired' nodes across many network states. © 2018 by John Wiley & Sons, Inc.