Literature DB >> 20007173

Computational limits to binary genes.

Nicolae Radu Zabet1, Dominique F Chu.   

Abstract

We analyse the trade-off between the speed with which a gene can propagate information, the noise of its output and its metabolic cost. Our main finding is that for any given level of metabolic cost there is an optimal trade-off between noise and processing speed. Any system with a non-vanishing leak expression rate is suboptimal, i.e. it will exhibit higher noise and/or slower speed than leak-free systems with the same metabolic cost. We also show that there is an optimal Hill coefficient h which minimizes noise and metabolic cost at fixed speeds, and an optimal threshold K which minimizes noise.

Mesh:

Year:  2009        PMID: 20007173      PMCID: PMC2871807          DOI: 10.1098/rsif.2009.0474

Source DB:  PubMed          Journal:  J R Soc Interface        ISSN: 1742-5662            Impact factor:   4.118


  24 in total

1.  Summing up the noise in gene networks.

Authors:  Johan Paulsson
Journal:  Nature       Date:  2004-01-29       Impact factor: 49.962

2.  Fast evaluation of fluctuations in biochemical networks with the linear noise approximation.

Authors:  Johan Elf; Måns Ehrenberg
Journal:  Genome Res       Date:  2003-11       Impact factor: 9.043

3.  Influence of catabolite repression and inducer exclusion on the bistable behavior of the lac operon.

Authors:  Moisés Santillán; Michael C Mackey
Journal:  Biophys J       Date:  2004-03       Impact factor: 4.033

4.  Noisy signal amplification in ultrasensitive signal transduction.

Authors:  Tatsuo Shibata; Koichi Fujimoto
Journal:  Proc Natl Acad Sci U S A       Date:  2004-12-29       Impact factor: 11.205

5.  Models of transcription factor binding: sensitivity of activation functions to model assumptions.

Authors:  Dominique Chu; Nicolae Radu Zabet; Boris Mitavskiy
Journal:  J Theor Biol       Date:  2008-12-10       Impact factor: 2.691

6.  Stochastic kinetic analysis of developmental pathway bifurcation in phage lambda-infected Escherichia coli cells.

Authors:  A Arkin; J Ross; H H McAdams
Journal:  Genetics       Date:  1998-08       Impact factor: 4.562

7.  Non-genetic individuality: chance in the single cell.

Authors:  J L Spudich; D E Koshland
Journal:  Nature       Date:  1976-08-05       Impact factor: 49.962

Review 8.  Protein molecules as computational elements in living cells.

Authors:  D Bray
Journal:  Nature       Date:  1995-07-27       Impact factor: 49.962

9.  Metabolic efficiency and amino acid composition in the proteomes of Escherichia coli and Bacillus subtilis.

Authors:  Hiroshi Akashi; Takashi Gojobori
Journal:  Proc Natl Acad Sci U S A       Date:  2002-03-19       Impact factor: 11.205

10.  Quantitative model for gene regulation by lambda phage repressor.

Authors:  G K Ackers; A D Johnson; M A Shea
Journal:  Proc Natl Acad Sci U S A       Date:  1982-02       Impact factor: 11.205

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  8 in total

1.  Facilitated diffusion buffers noise in gene expression.

Authors:  Armin P Schoech; Nicolae Radu Zabet
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2014-09-02

Review 2.  Homotypic clusters of transcription factor binding sites: A model system for understanding the physical mechanics of gene expression.

Authors:  Daphne Ezer; Nicolae Radu Zabet; Boris Adryan
Journal:  Comput Struct Biotechnol J       Date:  2014-08-01       Impact factor: 7.271

3.  Periodic synchronization of isolated network elements facilitates simulating and inferring gene regulatory networks including stochastic molecular kinetics.

Authors:  Johannes Hettich; J Christof M Gebhardt
Journal:  BMC Bioinformatics       Date:  2022-01-05       Impact factor: 3.169

4.  In silico evolution of diauxic growth.

Authors:  Dominique F Chu
Journal:  BMC Evol Biol       Date:  2015-09-29       Impact factor: 3.260

5.  The effects of transcription factor competition on gene regulation.

Authors:  Nicolae Radu Zabet; Boris Adryan
Journal:  Front Genet       Date:  2013-10-07       Impact factor: 4.599

6.  Physical constraints determine the logic of bacterial promoter architectures.

Authors:  Daphne Ezer; Nicolae Radu Zabet; Boris Adryan
Journal:  Nucleic Acids Res       Date:  2014-01-29       Impact factor: 16.971

7.  Gene switching rate determines response to extrinsic perturbations in the self-activation transcriptional network motif.

Authors:  Sebastiano de Franciscis; Giulio Caravagna; Giancarlo Mauri; Alberto d'Onofrio
Journal:  Sci Rep       Date:  2016-06-03       Impact factor: 4.379

8.  The lag-phase during diauxic growth is a trade-off between fast adaptation and high growth rate.

Authors:  Dominique Chu; David J Barnes
Journal:  Sci Rep       Date:  2016-04-29       Impact factor: 4.379

  8 in total

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