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Stochastic resonance in gene transcriptional regulatory system driven by Gaussian noise and Lévy noise

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  • Mi, Li-Na
  • Guo, Yong-Feng
  • Zhang, Meng
  • Zhuo, Xiao-Jing

Abstract

The impacts of noise parameters and input signal parameters on stochastic resonance are explored in a gene transcriptional regulatory model driven by a combination of multiplicative Gaussian noise and additive Lévy noise. The response time series and signal-to-noise ratios are obtained by numerical simulations to quantify the occurrence of stochastic resonance. It is shown that the Gaussian noise intensity can cause the stochastic resonance, while the Lévy noise intensity can cause both the stochastic resonance and inverse stochastic resonance. The increases of Gaussian noise intensity inhibits these two phenomena and enhances system stability. The changes of the Lévy noise intensity parameter can cause the system to switch between low and high concentration state. In addition, the stability index and skewness parameter of Lévy noise can also result in stochastic resonance. Therefore, the optimum stochastic resonance can be achieved and useful genetic information can be easily acquired by adjusting the noise parameters. Our findings should contribute in the selection of appropriate parameters to achieve stochastic resonance in gene transcriptional regulation models, laying the foundation for the selection of stochastic resonance parameter ranges in actual gene transcriptional engineering.

Suggested Citation

  • Mi, Li-Na & Guo, Yong-Feng & Zhang, Meng & Zhuo, Xiao-Jing, 2023. "Stochastic resonance in gene transcriptional regulatory system driven by Gaussian noise and Lévy noise," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    • Handle: RePEc:eee:chsofr:v:167:y:2023:i:c:s0960077922012759
    DOI: 10.1016/j.chaos.2022.113096
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    1. Andrew M. Edwards & Richard A. Phillips & Nicholas W. Watkins & Mervyn P. Freeman & Eugene J. Murphy & Vsevolod Afanasyev & Sergey V. Buldyrev & M. G. E. da Luz & E. P. Raposo & H. Eugene Stanley & Ga, 2007. "Revisiting Lévy flight search patterns of wandering albatrosses, bumblebees and deer," Nature, Nature, vol. 449(7165), pages 1044-1048, October.
    2. Jin, Yanfei & Xu, Wei & Xu, Meng, 2005. "Stochastic resonance in an asymmetric bistable system driven by correlated multiplicative and additive noise," Chaos, Solitons & Fractals, Elsevier, vol. 26(4), pages 1183-1187.
    3. D. Valenti & L. Schimansky-Geier & X. Sailer & B. Spagnolo, 2006. "Moment equations for a spatially extended system of two competing species," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 50(1), pages 199-203, March.
    4. Guarcello, C., 2021. "Lévy noise effects on Josephson junctions," Chaos, Solitons & Fractals, Elsevier, vol. 153(P2).
    5. G. Bonanno & D. Valenti & B. Spagnolo, 2005. "Role of Noise in a Market Model with Stochastic Volatility," Papers cond-mat/0510154, arXiv.org, revised Oct 2006.
    6. Zhao, Yu & Yuan, Sanling, 2016. "Stability in distribution of a stochastic hybrid competitive Lotka–Volterra model with Lévy jumps," Chaos, Solitons & Fractals, Elsevier, vol. 85(C), pages 98-109.
    7. Mikhaylov, A.N. & Guseinov, D.V. & Belov, A.I. & Korolev, D.S. & Shishmakova, V.A. & Koryazhkina, M.N. & Filatov, D.O. & Gorshkov, O.N. & Maldonado, D. & Alonso, F.J. & Roldán, J.B. & Krichigin, A.V. , 2021. "Stochastic resonance in a metal-oxide memristive device," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    8. Surazhevsky, I.A. & Demin, V.A. & Ilyasov, A.I. & Emelyanov, A.V. & Nikiruy, K.E. & Rylkov, V.V. & Shchanikov, S.A. & Bordanov, I.A. & Gerasimova, S.A. & Guseinov, D.V. & Malekhonova, N.V. & Pavlov, D, 2021. "Noise-assisted persistence and recovery of memory state in a memristive spiking neuromorphic network," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    9. Baronchelli, Andrea & Radicchi, Filippo, 2013. "Lévy flights in human behavior and cognition," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 101-105.
    10. A. Dubkov & B. Spagnolo, 2008. "Verhulst model with Lévy white noise excitation," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 65(3), pages 361-367, October.
    11. Valenti, D. & Fiasconaro, A. & Spagnolo, B., 2004. "Stochastic resonance and noise delayed extinction in a model of two competing species," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 331(3), pages 477-486.
    12. G. Bonanno & D. Valenti & B. Spagnolo, 2006. "Role of noise in a market model with stochastic volatility," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 53(3), pages 405-409, October.
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