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Volumn 29, Issue 18, 2013, Pages 2311-2319

The signal within the noise: Efficient inference of stochastic gene regulation models using fluorescence histograms and stochastic simulations

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; BAYES THEOREM; BIOLOGICAL MODEL; COMPUTER SIMULATION; FLOW CYTOMETRY; FLUORESCENCE; GENE EXPRESSION REGULATION; GENE REGULATORY NETWORK; STATISTICS; ARTICLE;

EID: 84883481038     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btt380     Document Type: Article
Times cited : (47)

References (32)
  • 1
    • 0031746834 scopus 로고    scopus 로고
    • New unstable variants of green fluorescent protein for studies of transient gene expression in bacteria
    • Andersen,J.B. et al. (1998) New unstable variants of green fluorescent protein for studies of transient gene expression in bacteria. Appl. Environ. Microbiol., 64, 2240-2246.
    • (1998) Appl. Environ. Microbiol. , vol.64 , pp. 2240-2246
    • Andersen, J.B.1
  • 2
    • 84863475698 scopus 로고    scopus 로고
    • A stochastic signaling network mediates the probabilistic induction of cerebellar long-term depression
    • Antunes,G. and De Schutter,E. (2012) A stochastic signaling network mediates the probabilistic induction of cerebellar long-term depression. J. Neurosci., 32, 9288-9300.
    • (2012) J. Neurosci. , vol.32 , pp. 9288-9300
    • Antunes, G.1    De Schutter, E.2
  • 3
    • 0031879114 scopus 로고    scopus 로고
    • Stochastic kinetic analysis of developmental pathway bifurcation in phage -infected Escherichia coli cells
    • Arkin,A. et al. (1998) Stochastic kinetic analysis of developmental pathway bifurcation in phage -infected Escherichia coli cells. Genetics, 149, 1633-1648.
    • (1998) Genetics , vol.149 , pp. 1633-1648
    • Arkin, A.1
  • 4
    • 1542267833 scopus 로고    scopus 로고
    • Global analysis of Escherichia coli RNA degradosome function using DNA microarrays
    • Bernstein,J.A. et al. (2004) Global analysis of Escherichia coli RNA degradosome function using DNA microarrays. Proc. Natl Acad. Sci. USA, 101, 2758-2763.
    • (2004) Proc. Natl Acad. Sci. USA , vol.101 , pp. 2758-2763
    • Bernstein, J.A.1
  • 5
    • 84860290293 scopus 로고    scopus 로고
    • Accelerated maximum likelihood parameter estimation for stochastic biochemical systems
    • Daigle,B.J. et al. (2012) Accelerated maximum likelihood parameter estimation for stochastic biochemical systems. BMC Bioinformatics, 13, 68.
    • (2012) BMC Bioinformatics , vol.13 , pp. 68
    • Daigle, B.J.1
  • 6
    • 0242490781 scopus 로고    scopus 로고
    • Fast evaluation of fluctuations in biochemical networks with the linear noise approximation
    • Elf,J. and Ehrenberg,M. (2003) Fast evaluation of fluctuations in biochemical networks with the linear noise approximation. Genome Res., 13, 2475-2484.
    • (2003) Genome Res. , vol.13 , pp. 2475-2484
    • Elf, J.1    Ehrenberg, M.2
  • 7
    • 0037119587 scopus 로고    scopus 로고
    • Stochastic gene expression in a single cell
    • Elowitz,M. et al. (2002) Stochastic gene expression in a single cell. Science, 297, 1183-1186.
    • (2002) Science , vol.297 , pp. 1183-1186
    • Elowitz, M.1
  • 8
    • 0034688173 scopus 로고    scopus 로고
    • A synthetic oscillatory network of transcriptional regulators
    • Elowitz,M.B. and Leibler,S. (2000) A synthetic oscillatory network of transcriptional regulators. Nature, 403, 335-338.
    • (2000) Nature , vol.403 , pp. 335-338
    • Elowitz, M.B.1    Leibler, S.2
  • 9
    • 0017030517 scopus 로고
    • A general method for numerically simulating the stochastic time evolution of coupled chemical reactions
    • Gillespie,D.T. (1976) A general method for numerically simulating the stochastic time evolution of coupled chemical reactions. J. Comput. Phys., 22, 403-434.
    • (1976) J. Comput. Phys. , vol.22 , pp. 403-434
    • Gillespie, D.T.1
  • 10
    • 33645429016 scopus 로고
    • Exact stochastic simulation of coupled chemical reactions
    • Gillespie,D.T. (1977) Exact stochastic simulation of coupled chemical reactions. J. Phys. Chem-US, 81, 2340-2361.
    • (1977) J. Phys. Chem-US , vol.81 , pp. 2340-2361
    • Gillespie, D.T.1
  • 11
    • 0034225547 scopus 로고    scopus 로고
    • The chemical Langevin equation
    • Gillespie,D.T. (2000) The chemical Langevin equation. J. Chem. Phys., 113, 297.
    • (2000) J. Chem. Phys. , vol.113 , pp. 297
    • Gillespie, D.T.1
  • 12
    • 84860901236 scopus 로고    scopus 로고
    • Bayesian parameter inference for stochastic biochemical network models using particle Markov chain Monte Carlo
    • Golightly,A. and Wilkinson,D.J. (2011) Bayesian parameter inference for stochastic biochemical network models using particle Markov chain Monte Carlo. Interface Focus, 1, 807-820.
    • (2011) Interface Focus , vol.1 , pp. 807-820
    • Golightly, A.1    Wilkinson, D.J.2
  • 13
    • 71749100925 scopus 로고    scopus 로고
    • Bayesian inference of biochemical kinetic parameters using the linear noise approximation
    • Komorowski,M. et al. (2009) Bayesian inference of biochemical kinetic parameters using the linear noise approximation. BMC Bioinformatics, 10, 343.
    • (2009) BMC Bioinformatics , vol.10 , pp. 343
    • Komorowski, M.1
  • 14
    • 84863564323 scopus 로고    scopus 로고
    • Calibrating spatio-temporal models of leukocyte dynamics against in vivo live-imaging data using approximate bayesian computation
    • Liepe,J. et al. (2012) Calibrating spatio-temporal models of leukocyte dynamics against in vivo live-imaging data using approximate bayesian computation. Integr. Biol., 4, 335-345.
    • (2012) Integr. Biol. , vol.4 , pp. 335-345
    • Liepe, J.1
  • 15
  • 16
    • 84870305264 scopus 로고    scopus 로고
    • Wisdom of crowds for robust gene network inference
    • Marbach,D. et al. (2012)Wisdom of crowds for robust gene network inference. Nat. Methods, 9, 796-804.
    • (2012) Nat. Methods , vol.9 , pp. 796-804
    • Marbach, D.1
  • 17
    • 4544367274 scopus 로고    scopus 로고
    • Evaluating Kolmogorov's distribution
    • Marsaglia,G. et al. (2003) Evaluating Kolmogorov's distribution. J. Stat. Softw., 8, 1-4.
    • (2003) J. Stat. Softw. , vol.8 , pp. 1-4
    • Marsaglia, G.1
  • 18
    • 50349086894 scopus 로고    scopus 로고
    • Timing and dynamics of single cell gene expression in the arabinose utilization system
    • Megerle,J.A. et al. (2008) Timing and dynamics of single cell gene expression in the arabinose utilization system. Biophys. J., 95, 2103-2115.
    • (2008) Biophys. J. , vol.95 , pp. 2103-2115
    • Megerle, J.A.1
  • 19
    • 33751347484 scopus 로고    scopus 로고
    • The finite state projection algorithm for the solution of the chemical master equation
    • Munsky,B. and Khammash,M. (2006) The finite state projection algorithm for the solution of the chemical master equation. J. Chem. Phys., 124, 044104.
    • (2006) J. Chem. Phys. , vol.124 , pp. 044104
    • Munsky, B.1    Khammash, M.2
  • 20
    • 73149105740 scopus 로고    scopus 로고
    • Listening to the noise: Random fluctuations reveal gene network parameters
    • Munsky,B. et al. (2009) Listening to the noise: Random fluctuations reveal gene network parameters. Mol. Syst. Biol., 5, 318.
    • (2009) Mol. Syst. Biol. , vol.5 , pp. 318
    • Munsky, B.1
  • 21
    • 84873801555 scopus 로고    scopus 로고
    • Systematic identification of signal-activated stochastic gene regulation
    • Neuert,G. et al. (2013) Systematic identification of signal-activated stochastic gene regulation. Science, 339, 584-587.
    • (2013) Science , vol.339 , pp. 584-587
    • Neuert, G.1
  • 22
    • 0036578645 scopus 로고    scopus 로고
    • Regulation of noise in the expression of a single gene
    • Ozbudak,E.M. et al. (2002) Regulation of noise in the expression of a single gene. Nat Genet, 31, 69-73.
    • (2002) Nat Genet , vol.31 , pp. 69-73
    • Ozbudak, E.M.1
  • 23
    • 0032735986 scopus 로고    scopus 로고
    • Population growth of human Y chromosomes: A study of Y chromosome microsatellites
    • Pritchard,J.K. et al. (1999) Population growth of human Y chromosomes: A study of Y chromosome microsatellites. Mol. Biol. Evol., 16, 1791-1798.
    • (1999) Mol. Biol. Evol. , vol.16 , pp. 1791-1798
    • Pritchard, J.K.1
  • 24
    • 33746582040 scopus 로고    scopus 로고
    • Parameter estimation in stochastic biochemical reactions
    • Reinker,S. et al. (2006) Parameter estimation in stochastic biochemical reactions. IEE Proc. Syst. Biol., 153, 168-178.
    • (2006) IEE Proc. Syst. Biol. , vol.153 , pp. 168-178
    • Reinker, S.1
  • 25
    • 79951586485 scopus 로고    scopus 로고
    • Approximate moment dynamics for chemically reacting systems
    • Singh,A. and Hespanha,J. (2011) Approximate moment dynamics for chemically reacting systems. IEEE T. Automat. Contr., 56, 414-418.
    • (2011) IEEE T Automat. Contr. , vol.56 , pp. 414-418
    • Singh, A.1    Hespanha, J.2
  • 26
    • 33845875759 scopus 로고    scopus 로고
    • Simulated maximum likelihood method for estimating kinetic rates in gene expression
    • Tian,T. et al. (2007) Simulated maximum likelihood method for estimating kinetic rates in gene expression. Bioinformatics, 23, 84-91.
    • (2007) Bioinformatics , vol.23 , pp. 84-91
    • Tian, T.1
  • 27
    • 58149142997 scopus 로고    scopus 로고
    • Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems
    • Toni,T. et al. (2009) Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems. J. R. Soc. Interface, 6, 187-202.
    • (2009) J. R. Soc. Interface , vol.6 , pp. 187-202
    • Toni, T.1
  • 28
    • 84862188059 scopus 로고    scopus 로고
    • Elucidating the in vivo phosphorylation dynamics of the erk map kinase using quantitative proteomics data and bayesian model selection
    • Toni,T. et al. (2012) Elucidating the in vivo phosphorylation dynamics of the erk map kinase using quantitative proteomics data and bayesian model selection. Mol. BioSyst., 8, 1921-1929.
    • (2012) Mol. BioSyst. , vol.8 , pp. 1921-1929
    • Toni, T.1
  • 29
    • 0033812363 scopus 로고    scopus 로고
    • Construction and characterization of a highly regulable expression vector, pLAC11, and its multipurpose derivatives, pLAC22 and pLAC33
    • Warren,J.W. et al. (2000) Construction and characterization of a highly regulable expression vector, pLAC11, and its multipurpose derivatives, pLAC22 and pLAC33. Plasmid, 44, 138-151.
    • (2000) Plasmid , vol.44 , pp. 138-151
    • Warren, J.W.1
  • 30
    • 22744441386 scopus 로고    scopus 로고
    • Stochastic gene expression in a lentiviral positive-feedback loop: HIV-1 Tat fluctuations drive phenotypic diversity
    • Weinberger,L.S. et al. (2005) Stochastic gene expression in a lentiviral positive-feedback loop: HIV-1 Tat fluctuations drive phenotypic diversity. Cell, 122, 169-182.
    • (2005) Cell , vol.122 , pp. 169-182
    • Weinberger, L.S.1
  • 31
    • 77955405541 scopus 로고    scopus 로고
    • Parameter inference for discretely observed stochastic kinetic models using stochastic gradient descent
    • Yuanfeng,W. et al. (2010) Parameter inference for discretely observed stochastic kinetic models using stochastic gradient descent. BMC Syst. Biol., 4, 99.
    • (2010) BMC Syst. Biol. , vol.4 , pp. 99
    • Yuanfeng, W.1
  • 32
    • 84861443923 scopus 로고    scopus 로고
    • Moment-based inference predicts bimodality in transient gene expression
    • Zechner,C. et al. (2012) Moment-based inference predicts bimodality in transient gene expression. Proc. Natl Acad. Sci. USA, 109, 8340-8345.
    • (2012) Proc. Natl Acad. Sci. USA , vol.109 , pp. 8340-8345
    • Zechner, C.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.