Source: Ma'ayan A, Jenkins SL, Neves S, Hasseldine A, Grace E, Dubin-Thaler B, Eungdamrong NJ, Weng G, Ram PT, Rice JJ, Kershenbaum A, Stolovitzky GA, Blitzer RD, Iyengar R. Formation of regulatory patterns during signal propagation in a Mammalian cellular network. Science. 2005 Aug 12;309(5737):1078-83.
We developed a model of 545 components (nodes) and 1259 interactions representing signaling pathways and cellular machines in the hippocampal CA1 neuron. Using graph theory methods, we analyzed ligand-induced signal flow through the system. Specification of input and output nodes allowed us to identify functional modules. Networking resulted in the emergence of regulatory motifs, such as positive and negative feedback and feedforward loops, that process information. Key regulators of plasticity were highly connected nodes required for the formation of regulatory motifs, indicating the potential importance of such motifs in determining cellular choices between homeostasis and plasticity.
PMID: 16099987 | PMCID: PMC3032439 | EndNote Citation
Some of the networks overall statistics are summarized in this page.
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.
A web-based interface that allows users to retrieve automatically generated pathways by selecting an extra-cellular ligand node/molecule and selecting a node that belongs toa cellular machine (i.e. transcription factor) as the target node/molecule. The program searches for all possible pathways that can reach the target molecule in the least number of steps and presents connection maps.
These include blocks of source code and text files used in this study, as well as Excel spreadsheet tables with the results.