DyNet: visualization and analysis of dynamic molecular interaction networks.

UNLABELLED: : The ability to experimentally determine molecular interactions on an almost proteome-wide scale under different conditions is enabling researchers to move from static to dynamic network analysis, uncovering new insights into how interaction networks are physically rewired in response to different stimuli and in disease. Dynamic interaction data presents a special challenge in network biology. Here, we present DyNet, a Cytoscape application that provides a range of functionalities for the visualization, real-time synchronization and analysis of large multi-state dynamic molecular interaction networks enabling users to quickly identify and analyze the most 'rewired' nodes across many network states. AVAILABILITY AND IMPLEMENTATION: DyNet is available at the Cytoscape (3.2+) App Store (http://apps.cytoscape.org/apps/dynet). CONTACT: david.lynn@sahmri.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Analysis and Visualization of Dynamic Networks Using the DyNet App for Cytoscape.

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.

Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks.

Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT), which enables users to easily construct and visualize a network of interactions from a gene list of interest, integrate contextual information, such as gene expression data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes that are differentially expressed) than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that such contextual hubs are considerably more biologically relevant than degree-based hubs and that analyses which rely on the identification of hubs solely based on their connectivity may be biased towards nodes that are highly connected in general rather than in the specific context of interest. AVAILABILITY: CHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store (http://apps.cytoscape.org/apps/chat).