Stochastic resonance in the gene transcriptional regulatory system subjected to noises

doi:10.1088/1674-1056/19/3/030503

中国物理B ›› 2010, Vol. 19 ›› Issue (3): 30503-030503.doi: 10.1088/1674-1056/19/3/030503

Stochastic resonance in the gene transcriptional regulatory system subjected to noises

王参军

Nonlinear Research Institute, Baoji University of Arts and Sciences, Baoji 721007, China

收稿日期:2009-05-24 修回日期:2009-08-30 出版日期:2010-03-15 发布日期:2010-03-15
基金资助:
Project supported by the National Natural Science Foundation of China (Grant No.~10865006), the Science Foundation of the Education Bureau of Shaanxi Province of China (Grant No.~09JK331) and the Science Foundation of Baoji University of Science and Arts of China (Grant No.~Zk0834).

Stochastic resonance in the gene transcriptional regulatory system subjected to noises

Wang Can-Jun(王参军)^†

Nonlinear Research Institute, Baoji University of Arts and Sciences, Baoji 721007, China

Received:2009-05-24 Revised:2009-08-30 Online:2010-03-15 Published:2010-03-15
Supported by:
Project supported by the National Natural Science Foundation of China (Grant No.~10865006), the Science Foundation of the Education Bureau of Shaanxi Province of China (Grant No.~09JK331) and the Science Foundation of Baoji University of Science and Arts of China (Grant No.~Zk0834).

摘要/Abstract

摘要： We have investigated in the adiabatic limit the phenomenon of stochastic resonance in the gene transcriptional regulatory system subjected to an additive noise, a multiplicative noise, and a weakly periodic signal. Using the general two-state approach for the asymmetry system, the analytic expression of signal-to-noise ratio is obtained. The effects of the additive noise intensity α, the multiplicative noise intensity D and the amplitude of input periodic signal A on the signal-to-noise ratio are analysed by numerical calculation. It is found that the existence of a maximum in the R_SNR--α and R_SNR--D plots is the identifying characteristic of the stochastic resonance phenomenon in the weakened noise intensity region. The stochastic resonance phenomena are restrained with increasing α and D, and enhanced with increasing A.

Abstract: We have investigated in the adiabatic limit the phenomenon of stochastic resonance in the gene transcriptional regulatory system subjected to an additive noise, a multiplicative noise, and a weakly periodic signal. Using the general two-state approach for the asymmetry system, the analytic expression of signal-to-noise ratio is obtained. The effects of the additive noise intensity α, the multiplicative noise intensity D and the amplitude of input periodic signal A on the signal-to-noise ratio are analysed by numerical calculation. It is found that the existence of a maximum in the R_SNR--$\alpha$ and R_SNR--D plots is the identifying characteristic of the stochastic resonance phenomenon in the weakened noise intensity region. The stochastic resonance phenomena are restrained with increasing $\alpha$ and D, and enhanced with increasing A.

Key words: gene transcriptional regulatory system, stochastic resonance, noises

中图分类号: (Noise)

05.40.Ca

王参军. Stochastic resonance in the gene transcriptional regulatory system subjected to noises[J]. 中国物理B, 2010, 19(3): 30503-030503.

Wang Can-Jun(王参军). Stochastic resonance in the gene transcriptional regulatory system subjected to noises[J]. Chin. Phys. B, 2010, 19(3): 30503-030503.

参考文献 39

[1]	Benzi R, Sutera A and Vulpiani A 1981 J. Phys. A 14 453
[2]	Nicolis C and Nicolis G 1981 Tellus 33 225
[3]	Gammaitoni L, H?nggi P, Jung P and Marchesoni F 1998 Rev. Mod. Phys. 70223
[4]	McNamara B and Wiesenfeld K 1989 Phys. Rev. A 39 4854
[5]	Jia Y, Zheng X P, Hu X M and Li J R 2001 Phys.Rev. E 63 031107
[6]	Ning L J and Xu W 2007 Acta Phys. Sin. 56 1944 (in Chinese)
[7]	Luo XQ and Zhu S Q 2004 Chin. Phys. 13 1201
[8]	Valenti D, Fiasconaro A and Spagnolo B 2004 Physica A 331 477
[9]	Zhong S and Xin H W 2001 Chem. Phys. Lett. 333 133
[10]	Zhang L Y, Jin G X and Cao L 2008 Acta Phys. Sin. 57 4706 (in Chinese)
[11]	Li J H 2002 Phys. Rev. E 66 031104
[12]	Kang Y M, Xu J X and Xie Y 2003 Acta Phys. Sin. 52 2712 (inChinese)
[13]	Hu G, Nicolis G and Nicolis C 1990 Phys. Rev. A 42 2030
[14]	Ning L J, Xu W and Yao M L 2008 Chin. Phys. B 17 0486
[15]	Hu G 1994 Stochastic Forces and Nonlinear Systems (Shanghai: Shanghai Scientfic andTechnological Education Publishing House) (in Chinese)
[16]	Douglass J K, Wilkens L, Pantazelou E and Moss F 1993 Nature 365 337
[17]	Russel D F,Wilkens L and Moss F 1999 Nature 402 291
[18]	Simonotto E, Riani M, Seife C, Roberts M, Twitty J and Moss F 1997 Phys. Rev. Lett. 78 1186
[19]	Zhong W R, Shao Y Z and He Z H 2006 Phys. Rev.E 73 060902(R)
[20]	Braun H A, Wissing H, Schafer K and Hirsch M C 1994 Nature 367 270
[21]	Ozbudak E M, Thattai M, Kurtser I, Grossman A D and van Oudenaarden A 2005Nature Genetics 37 937
[22]	Thattai M and van Oudenaarden A 2001 PNAS 98 8614
[23]	Swain P S, Elowitz M B and Siggia E D 2002 PNAS 99 12795
[24]	Paulsson J 2004 Nature 427 415
[25]	Raser J M and O'Shea E K 2005 Science 309 2010
[26]	Becskei A, Kaufmann B B and van Oudenaarden A 2002 Nature Genetics 31 69
[27]	Smolen P, Baxter D A and Byrne J H 1998 Am. J. Physiol. 274 C531
[28]	Smolen P, Baxter D A and Byrne J H 1999Am. J. Physiol. 277 C777
[29]	Wang J Y, Zhu C L, Jia Yand Li J R 2006 Chin. Phys. Lett. 23 1398
[30]	Liu Q and Jia Y 2004 Phys. Rev. E 70 041907
[31]	Wang C J and Mei D C 2008 Acta Phys. Sin. 57 3983 (in Chinese)
[32]	Zeng C H and Xie C W 2008 Phys. Scr. 78 035801
[33]	Zeng C H and Xie C W 2008 Chin. Phys.Lett. 25 1587
[34]	Loinger A, Lipshtat A, Balaban Q N and Biham O 2007 Phys. Rev. E 75 021904
[35]	Wio H S and Bouzat S 1999 Braz. J. Phys. 29 136
[36]	Li J H and Huang Z Q 1998 Phys. Rev. E 57 3917
[37]	Li J H 2007 Phys. Rev. E 76 031120
[38]	Wu D J, Cao L and Ke S Z 1994 Phys. Rev. E 50 2496
[39]	Li J H and Huang Z Q 1996 Phys. Rev. E 53 3315

Stochastic resonance in the gene transcriptional regulatory system subjected to noises

Stochastic resonance in the gene transcriptional regulatory system subjected to noises

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