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Stochastic noise in auto-regulatory genetic network: Model-dependence and statistical complication

Stochastic noise in auto-regulatory genetic network: Model-dependence and statistical complication For the single gene network model, there are two basic types. For convenience, we call them Type I and Type II, respectively. The Type I model describes both the dynamics of mRNA and protein. The Type II model is a simplification of the Type I model based on the assumption that the change rate of mRNA is much faster than protein because the half-life of mRNA is short compared with that of protein. the Type II model describes only the dynamics of protein. The analysis of the Type I model is based on the assumption that the ratio of the protein decay rate to the mRNA decay rate is small enough. The main results for Type I model show that the Fano factor of the protein must be bigger than one if there is no negative feedback on the transcription. If there is negative feedback, the relative fluctuation strength in the number of proteins is determined by the size of the feedback regulation strength. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Acta Mathematicae Applicatae Sinica Springer Journals

Stochastic noise in auto-regulatory genetic network: Model-dependence and statistical complication

Acta Mathematicae Applicatae Sinica , Volume 24 (4) – Oct 12, 2008

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Publisher
Springer Journals
Copyright
Copyright © 2008 by Institute of Applied Mathematics, Academy of Mathematics and System Sciences, Chinese Academy of Sciences and Springer-Verlag GmbH
Subject
Mathematics; Applications of Mathematics; Math Applications in Computer Science; Theoretical, Mathematical and Computational Physics
ISSN
0168-9673
eISSN
1618-3932
DOI
10.1007/s10255-005-5179-7
Publisher site
See Article on Publisher Site

Abstract

For the single gene network model, there are two basic types. For convenience, we call them Type I and Type II, respectively. The Type I model describes both the dynamics of mRNA and protein. The Type II model is a simplification of the Type I model based on the assumption that the change rate of mRNA is much faster than protein because the half-life of mRNA is short compared with that of protein. the Type II model describes only the dynamics of protein. The analysis of the Type I model is based on the assumption that the ratio of the protein decay rate to the mRNA decay rate is small enough. The main results for Type I model show that the Fano factor of the protein must be bigger than one if there is no negative feedback on the transcription. If there is negative feedback, the relative fluctuation strength in the number of proteins is determined by the size of the feedback regulation strength.

Journal

Acta Mathematicae Applicatae SinicaSpringer Journals

Published: Oct 12, 2008

References