Literature DB >> 15790857

Noise propagation in gene networks.

Juan M Pedraza1, Alexander van Oudenaarden.   

Abstract

Accurately predicting noise propagation in gene networks is crucial for understanding signal fidelity in natural networks and designing noise-tolerant gene circuits. To quantify how noise propagates through gene networks, we measured expression correlations between genes in single cells. We found that noise in a gene was determined by its intrinsic fluctuations, transmitted noise from upstream genes, and global noise affecting all genes. A model was developed that explains the complex behavior exhibited by the correlations and reveals the dominant noise sources. The model successfully predicts the correlations as the network is systematically perturbed. This approach provides a step toward understanding and manipulating noise propagation in more complex gene networks.

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Year:  2005        PMID: 15790857     DOI: 10.1126/science.1109090

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  296 in total

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Journal:  Science       Date:  2010-09-24       Impact factor: 47.728

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Journal:  Proc Natl Acad Sci U S A       Date:  2011-10-24       Impact factor: 11.205

5.  Identifying sources of variation and the flow of information in biochemical networks.

Authors:  Clive G Bowsher; Peter S Swain
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Review 6.  The role of physiological heterogeneity in microbial population behavior.

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Journal:  Nat Chem Biol       Date:  2010-09-17       Impact factor: 15.040

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Journal:  Biophys J       Date:  2010-05-19       Impact factor: 4.033

8.  Using a single fluorescent reporter gene to infer half-life of extrinsic noise and other parameters of gene expression.

Authors:  Michał Komorowski; Bärbel Finkenstädt; David Rand
Journal:  Biophys J       Date:  2010-06-16       Impact factor: 4.033

9.  Ribozyme-based insulator parts buffer synthetic circuits from genetic context.

Authors:  Chunbo Lou; Brynne Stanton; Ying-Ja Chen; Brian Munsky; Christopher A Voigt
Journal:  Nat Biotechnol       Date:  2012-10-03       Impact factor: 54.908

10.  Robust, tunable genetic memory from protein sequestration combined with positive feedback.

Authors:  Tatenda Shopera; William R Henson; Andrew Ng; Young Je Lee; Kenneth Ng; Tae Seok Moon
Journal:  Nucleic Acids Res       Date:  2015-09-17       Impact factor: 16.971

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