Signaling Analysis and Visualization 2.5

The discovery process of cellular signal transduction pathways has reached a stage where pathways are combined to form large networks of interactions. Viewing protein-protein and ligand-protein interactions as graphs (networks) where bio-molecules are represented as vertices (nodes) and interactions are represented as edges (links) is becoming increasingly popular. The emergence of datasets of large-scale networks made of cellular components and interactions provides the opportunity for statistical topological analysis and the challenge of network visualization. Graph-theory methods applied to complex systems in other fields is also applied to analyze bio-molecular cellular networks.

SAVI is a desktop application that implements standard methods to compute the clustering, diameter, connectivity distribution and detecting and visualizing network motifs. Additionally, SAVI generates a complete website from network datasets in text format. SAVI contains a tool called pathway-generator. This tool creates signaling connection maps as web pages from large datasets of interactions.