Biology – Quantitative Biology – Molecular Networks
Scientific paper
2007-11-03
Axelsen JB, Krishna S & Sneppen K, Stat. Mech. (2008) P01018
Biology
Quantitative Biology
Molecular Networks
21 pages, 6 figures
Scientific paper
10.1088/1742-5468/2008/01/P01018
In systems biology new ways are required to analyze the large amount of existing data on regulation of cellular processes. Recent work can be roughly classified into either dynamical models of well-described subsystems, or coarse-grained descriptions of the topology of the molecular networks at the scale of the whole organism. In order to bridge these two disparate approaches one needs to develop simplified descriptions of dynamics and topological measures which address the propagation of signals in molecular networks. Here, we consider the directed network of protein regulation in E. coli, characterizing its modularity in terms of its potential to transmit signals. We demonstrate that the simplest measure based on identifying sub-networks of strong components, within which each node could send a signal to every other node, indeed partitions the network into functional modules. We then suggest measures to quantify the cost and spread associated with sending a signal between any particular pair of proteins. Thereby, we address the signalling specificity within and between modules, and show that in the regulation of E.coli there is a systematic reduction of the cost and spread for signals traveling over more than two intermediate reactions.
Axelsen Jacob Bock
Krishna Sandeep
Sneppen Kim
No associations
LandOfFree
Cost and Capacity of Signaling in the Escherichia coli Protein Reaction Network does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Cost and Capacity of Signaling in the Escherichia coli Protein Reaction Network, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Cost and Capacity of Signaling in the Escherichia coli Protein Reaction Network will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-508107