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.
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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 a useful method for consolidating and organizing experimental evidence from multiple sources to achieve system-level understanding of how pathways control cellular phenotypes.
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 program 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 PathwayGenerator. This tool creates signaling connection maps as web pages from large datasets of interactions. SAVI can also generate a network of interactions when given a list of human gene names.
Requirements
Signaling Analysis and Visual
tags
analysis and and interactions are represented

Download Signaling Analysis and Visualization 2.5
Download Signaling Analysis and Visualization 2.5
Authors software
SigInt 1.0
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Signaling Analysis and Visualization 2.5
Mount Sinai School of Medicine Iyengar Lab
The discovery process of cellular signal transduction pathways has reached a stage where pathways are combined to form large networks of interactions.
Genes2Networks 1.0
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Genes2Networks is a command-line software utility that can be used to place lists of mammalian genes in the context of a background mammalian signalome and interactome networks.
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