Construction, Analysis and Visualization of a Large-scale Signaling Network in Hippocampal Neuronal Mammalian Cells

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. This website is dedicated to presenting parts of a research project related to network analysis with graph-theory and network visualization conducted at the Iyengar Laboratory in the Department of Pharmacology and Biological Chemistry at Mount Sinai School of Medicine in New York, NY.

Index of Nodes

Alphabetized List | Classified by Cellular Machines
List of nodes (signaling molecules that make up the network) composing the pathways and the network of interactions.

Network Statistics

Some of the network’s overall statistics are summarized in this page.

Network Motifs

Visualization of all the identified network motifs of the types: feedback and feedforward loops of sizes 3 and 4, bifans and scaffold motifs found in the network.

Supplementary Files

These include blocks of source code and text files used in this study, as well as Excel spreadsheet tables with the results.

Except where noted, all questions related to software and datasets should be directed to avi.maayan@mssm.edu, biological queries should be addressed to ravi.iyengar@mssm.edu.