Steady-state expression of self-regulated genes

Bioinformatics

Volumn 23, Issue 23, 2007, Pages 3185-3192

  Fournier, T ^a   Gabriel, J P ^a   Mazza, Christian ^a   Pasquier, J ^a   Galbete, J L ^b   Mermod, N ^b  

^a UNIVERSITY OF FRIBOURG   (Switzerland)

^b UNIVERSITY OF LAUSANNE   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BIOINFORMATICS; CELL FUNCTION; COMPUTER ANALYSIS; COMPUTER MODEL; FEEDBACK SYSTEM; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENE FUNCTION; GENE STRUCTURE; GENETIC ALGORITHM; GENETIC REGULATION; MONTE CARLO METHOD; PRIORITY JOURNAL; STEADY STATE; STOCHASTIC MODEL;

MAMMALIA;

EID: 36549083377     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/btm490     Document Type: Article

References (40)

1. Adalsteinsson,D. et al. (2004) Biochemical Network Stochastic Simulator (BioNetS): Software for stochastic modeling of biochemical networks. BMC Bioinformatics, 5, 24.
2. Arkin,A. et al. (1998) Stochastic kinetic analysis of developmental pathway bifurcation in phage lambda-infected escherichia coli cells. Genetics, 149, 1633-1648.
3. Austin,D.W. et al. (2005) Gene network shaping of inherent noise spectra. Nature, 439, 608-611.
4. Becskei,A. et al. (2001) Positive feedback in eukaryotic gene networks: Cell differentiation by graded to binary response conversion. EMBO J., 20, 2528-2535.
5. Blake,W.J. and CoUins,J.J. (2005) And the noise played on: Stochastic gene expression and HIV-1 infection. Cell, 122, 147-149.
6. Blake,W.J. et al. (2003) Noise in eukaryotic gene expression. Nature, 422, 633-637.
7. Blake,W.J. et al. (2006) Phenotypic consequences of promoter-mediated transcriptional noise. Mol. Cell, 24, 853-865.
8. Bolthausen,E. and Goldsheid,I. (2000) Recurrence and transience of random walks in random environments on a strip. Commun. Math. Phys. 214, 429-447.
9. Bratsun,D. et al. (2005) Delay-induced stochastic oscillations in gene regulation. Proc. Natl. Acad. Sci. USA, 102, 14593-14598. Comparative Study.
10. Burrage,K. et al. (2004) A multi-scaled approach for simulating chemical reaction systems. Prog. Biophys. Mol. Biol., 85, 217-234. Comparative Study.
11. Cao,Y. et al. (2005a) Multiscale stochastic simulation algorithm with stochastic partial equilibrium assumption for chemically reacting systems. J. Comput. Phys., 206, 395-411.
12. Cao,Y. et al. (2005b) The slow-scale stochastic simulation algorithm. J. Chem. Phys., 122, 14116.
13. Chatterjee et al. (2007) An overview of spatial microscopic and accelerated kinetic monte carlo methods. J. Comput. Aid. Mater. Des. 14, 253-308.
14. Chubb,J.R. et al. (2006) Transcriptional pulsing of a developmental gene. Curr. Biol., 16, 1018-1025.
15. El Samad,H. et al. (2005) Stochastic modelling of gene regulatory networks. Int. J. Robust Nonlinear Control, 15, 691-711.
16. Erban,R. et al. (2006) Gene regulatory networks: A coarse-grained, equation-free approach to multiscale computation. J. Chem. Phys., 124, 084106.
17. Gillespie,D.T. (1977) Exact stochastic simulation of coupled chemical reactions. J. Phys. Chem., 81, 2340-2361.
18. Gillespie,D.T. (2001) Approximate accelerated stochastic simulation of chemically reacting systems. J. Chem. Phys., 115, 1716-1733.
19. Goutsias,J. (2005) Quasiequilibrium approximation of fast reaction kinetics in stochastic biochemical systems. J. Chem. Phys., 122 184102.
20. Goutsias,J. and Kim,S. (2006) Stochastic transcriptional regulatory systems with time delays: A mean-field approximation. J. Comput. Biol., 13, 1049-1076.
21. Guido,N.J. et al. (2006) A bottom-up approach to gene regulation. Nature, 439, 856-860.
22. Homos,J.E.M. et al. (2005) Self-regulating gene: An exact solution. Phys. Rev. E Stat. Nonlin. Soft. Matter. Phys., 72 (5 Pt 1), 051907.
23. Imhof,M.O. et al. (2000) A regulatory network for the efficient control of transgene expression. J. Gene Med., 2, 107-116.
24. Isaacs,F.J. et al. (2003) Prediction and measurement of an autoregulatory genetic module. Proc. Natl. Acad. Sci. USA, 100 7714-7719.
25. Kaern,M. et al. (2005) Stochasticity in gene expression: From theories to phenotypes. Nat. Rev. Genet., 6, 451-464.
26. Kepler,T.B. and Elston,T.C. (2001) Stochasticity in transcriptional regulation: Origins, consequences, and mathematical representations. Biophys. J., 81, 3116-3136.
27. Mcadams,H. H. and Arkin,A. (1997) Stochastic mechanisms in gene expression. Proc. Natl. Acad. Sci. USA, 94, 814-819.
28. Ozbudak,E.M. et al. (2002) Regulation of noise in the expression of a single gene. Nat. Genet., 31, 69-73.
29. Paulsson,J. (2004) Summing up the noise in gene networks. Nature, 427, 415-418.
30. Paulsson,J. (2005) Models of stochastic gene expression. Phys. Life Rev., 2, 157-175.
31. Pedraza,J.M. and van Oudenaarden,A. (2005) Noise propagation in gene networks. Science, 307, 1965-1969.
32. Raj,A. et al. (2006) Stochastic mrna synthesis in mammalian cells. PLoS Biol., 4, 1707-1719.
33. Raser,J.M. and O'Shea,E.K. (2004) Control of stochasticity in eukaryotic gene expression. Science, 304, 1811-1814.
34. Salis,H. and Kaznessis,Y. (2005) Accurate hybrid stochastic simulation of a system of coupled chemical or biochemical reactions. J. Chem. Phys., 122, 054103.
35. Salis,H. et al. (2006) Multiscale hy3s: Hybrid stochastic simulation for supercomputers. BMC Bioinfomatics, 7, 93.
36. Sato,N. et al. (2004) Fluctuation of chromatin unfolding associated with variation in the level of gene expression. Genes Cells, 9, 619-630.
37. Shibata,T. (2003a) Fluctuating reaction rates and their application to problems of gene expression. Phys. Rev. E, 67, 061906.
38. Shibata,T. (2003b) Reducing the master equations for noisy chemical reactions. The J. Chem. Phys., 119, 6629-6634.
39. Sotiropoulos,V. and Kaznessis,Y.N. (2007) Synthetic tetracycline-inducible regulatory networks: Computer-aided design of dynamic phenotypes. BMC Syst. Biol., 1, 7.
40. 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.