Literature DB >> 15135030

Noise-reduction through interaction in gene expression and biochemical reaction processes.

Yoshihiro Morishita1, Kazuyuki Aihara.   

Abstract

We demonstrate that interaction in gene expression and biochemical reaction processes has a significant influence on reducing fluctuations. Especially, we have found that the interaction between synthesized proteins and background molecules can reduce the fluctuation level in gene expression, which is a counter example to the intuition that background factors disturb information processing in genetic networks by increasing the noise level. This fact also indicates that the macromolecular crowding observed in actual cells can contribute to reduce the noise level. In addition, the noise-reduction phenomenon is not limited to the interaction between the proteins and background molecules, but can be applied to other reactions such as a dimerization process and the coupling of reactions with large fluctuations by intrinsic noise. Finally, on the basis of these results, we propose a new and plausible method for reducing the fluctuations generated in synthesized genetic networks, and also discuss the applicability of this method to the stabilization of system dynamics by using a toggle switch model.

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Year:  2004        PMID: 15135030     DOI: 10.1016/j.jtbi.2004.01.007

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  10 in total

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2.  An optimal number of molecules for signal amplification and discrimination in a chemical cascade.

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3.  Multiscale Modeling of Cellular Epigenetic States: Stochasticity in Molecular Networks, Chromatin Folding in Cell Nuclei, and Tissue Pattern Formation of Cells.

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4.  Control of transcriptional variability by overlapping feed-forward regulatory motifs.

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Review 5.  Transcriptional noise and cellular heterogeneity in mammalian macrophages.

Authors:  S Ramsey; A Ozinsky; A Clark; K D Smith; P de Atauri; V Thorsson; D Orrell; H Bolouri
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2006-03-29       Impact factor: 6.237

6.  Hybrid stochastic simulations of intracellular reaction-diffusion systems.

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7.  Quantifying intrinsic and extrinsic variability in stochastic gene expression models.

Authors:  Abhyudai Singh; Mohammad Soltani
Journal:  PLoS One       Date:  2013-12-31       Impact factor: 3.240

8.  ceRNA crosstalk stabilizes protein expression and affects the correlation pattern of interacting proteins.

Authors:  Araks Martirosyan; Andrea De Martino; Andrea Pagnani; Enzo Marinari
Journal:  Sci Rep       Date:  2017-03-07       Impact factor: 4.379

9.  Elucidating the sources of β-catenin dynamics in human neural progenitor cells.

Authors:  Orianne Mazemondet; Mathias John; Stefan Leye; Arndt Rolfs; Adelinde M Uhrmacher
Journal:  PLoS One       Date:  2012-08-20       Impact factor: 3.240

10.  Optimal enumeration of state space of finitely buffered stochastic molecular networks and exact computation of steady state landscape probability.

Authors:  Youfang Cao; Jie Liang
Journal:  BMC Syst Biol       Date:  2008-03-29
  10 in total

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