DocumentCode :
1121646
Title :
Determination of critical network interactions: an augmented Boolean pseudo-dynamics approach
Author :
Soni, A.S. ; Jenkins, J.W. ; Sundaram, S.S.
Author_Institution :
Biomed. Technol. Div., CFD Res. Corp., Huntsville, AL
Volume :
2
Issue :
2
fYear :
2008
fDate :
3/1/2008 12:00:00 AM
Firstpage :
55
Lastpage :
63
Abstract :
Network theory has established that highly connected nodes in regulatory networks (hubs) show a strong correlation with criticality in network function. Although topological analysis is fully capable of identifying network hubs, it does not provide an objective method for ranking the importance of a particular node by relating its contribution to the overall network response. Towards this end, the authors have developed an augmented Boolean pseudo-dynamics approach to a priori determine the critical network interactions in biological interaction networks. The approach utilises network topology and dynamic state information to determine the set of active pathways. The active pathways are used in conjunction with the key cellular properties of efficiency and robustness, to rank the network interactions based on their importance in the sustenance of network function. To demonstrate the utility of the approach, the authors consider the well characterised guard cell signalling network in plant cells. An integrated analysis of the network revealed the critical mechanisms resulting in stomata closure in the presence and absence of abscisic acid, in excellent agreement with published results.
Keywords :
Boolean algebra; biomembrane transport; botany; cellular biophysics; molecular biophysics; network theory (graphs); network topology; nonlinear dynamical systems; abscisic acid; augmented Boolean pseudo-dynamics approach; biological interaction networks; critical network interaction determination; critical network interactions; dynamic state information; guard cell signalling network; network function criticality; network theory; network topology; node importance ranking; overall network response node contribution; plant cells; regulatory network highly connected nodes;
fLanguage :
English
Journal_Title :
Systems Biology, IET
Publisher :
iet
ISSN :
1751-8849
Type :
jour
DOI :
10.1049/iet-syb:20070025
Filename :
4483539
Link To Document :
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