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  Limits of noise for autoregulated gene expression

Czuppon, P., & Pfaffelhuber, P. (2018). Limits of noise for autoregulated gene expression. Journal of Mathematical Biology, 77(4), 1153-1191. doi:10.1007/s00285-018-1248-4.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0002-6BE2-7 Version Permalink: http://hdl.handle.net/21.11116/0000-0002-6BE3-6
Genre: Journal Article

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Czuppon, Peter1, Author              
Pfaffelhuber, Peter, Author
Affiliations:
1Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society, ou_1445641              

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Free keywords: Intrinsic noise; Langevin approximation; Quasi-steady-state assumption; Chemical reaction network; Auto-regulated gene expression
 Abstract: Gene expression is influenced by extrinsic noise (involving a fluctuating environment of cellular processes) and intrinsic noise (referring to fluctuations within a cell under constant environment). We study the standard model of gene expression including an (in-)active gene, mRNA and protein. Gene expression is regulated in the sense that the protein feeds back and either represses (negative feedback) or enhances (positive feedback) its production at the stage of transcription. While it is well-known that negative (positive) feedback reduces (increases) intrinsic noise, we give a precise result on the resulting fluctuations in protein numbers. The technique we use is an extension of the Langevin approximation and is an application of a central limit theorem under stochastic averaging for Markov jump processes (Kang et al. in Ann Appl Probab 24:721–759, 2014). We find that (under our scaling and in equilibrium), negative feedback leads to a reduction in the Fano factor of at most 2, while the noise under positive feedback is potentially unbounded. The fit with simulations is very good and improves on known approximations.

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Language(s): eng - English
 Dates: 2018-05-062017-09-052018-05-242018
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1007/s00285-018-1248-4
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Title: Journal of Mathematical Biology
Source Genre: Journal
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Publ. Info: Heidelberg : Springer
Pages: - Volume / Issue: 77 (4) Sequence Number: - Start / End Page: 1153 - 1191 Identifier: ISSN: 0303-6812
CoNE: https://pure.mpg.de/cone/journals/resource/954925511424