DocumentCode :
3159503
Title :
Measuring the degree of modularity in gene regulatory networks from the relaxation of finite perturbations
Author :
Kyung Hyuk Kim ; Sauro, H.M.
Author_Institution :
Dept. of Bioeng., Univ. of Washington, Seattle, WA, USA
fYear :
2012
fDate :
10-13 Dec. 2012
Firstpage :
5330
Lastpage :
5335
Abstract :
In gene regulatory networks, transcription factors regulate downstream sites by binding or unbinding to specific promoter regions. It is known that the binding-unbinding process can affect factor life times, and thus response times. This change in the dynamical properties depends on the number of sites that the transcription factor binds to as well as the factor concentration level. To estimate how the dynamics of a given transcription factor will be affected by the number of binding sites, we previously devised a measure called the fan-out - complimentary measure to retroactivity - that indicates the maximum number of the binding sites before the dynamic response is significantly affected. We provided an efficient method to measure the fan-out and retroactivity experimentally by exploiting gene expression noise. In this presentation, we provide another efficient measurement method for retroactivity and fan-out at the population level. The method resorts to finite-size perturbations in system parameters or concentrations. The equivalent analysis method at the single cell level that is based on gene expression noise is also presented.
Keywords :
genetics; molecular biophysics; binding site; binding-unbinding process; factor concentration level; factor life time; fan-out measure; finite perturbation; gene expression noise; gene regulatory network; modularity degree; promoter region; response time; retroactivity measure; single cell level; transcription factor; Gene expression; Noise; Sociology; Statistics; Time factors; Time measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
Conference_Location :
Maui, HI
ISSN :
0743-1546
Print_ISBN :
978-1-4673-2065-8
Electronic_ISBN :
0743-1546
Type :
conf
DOI :
10.1109/CDC.2012.6425827
Filename :
6425827
Link To Document :
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