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The influence of internal noise on the detection of hormonal signal with the existence of external noise in a cell system

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  • Li, Hongying
  • Yao, Chengli

Abstract

In recent years, the constructive role of internal noise in mesoscopic system has attracted much attention. Because the external noise is also unavoidable, it is more practical to study the influence of internal noise with the existence of external noise in these systems. By constructing a mesoscopic stochastic model of a cell system, we discussed the influence of internal noise on the detection of hormonal signal with the existence of external noise. Results have found that internal noise can play a constructive role when external noise intensity is at some regions (D < 1.0 and D > 1.16), so that the cell system can effectively detect the weak hormonal signal through intracellular calcium spikes. This phenomenon is different from the results found previously, where it was found that internal noise always played a destructive role except for at very small external noise intensity.

Suggested Citation

  • Li, Hongying & Yao, Chengli, 2017. "The influence of internal noise on the detection of hormonal signal with the existence of external noise in a cell system," Applied Mathematics and Computation, Elsevier, vol. 314(C), pages 1-6.
    • Handle: RePEc:eee:apmaco:v:314:y:2017:i:c:p:1-6
    DOI: 10.1016/j.amc.2017.06.021
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    1. William J. Blake & Mads KÆrn & Charles R. Cantor & J. J. Collins, 2003. "Noise in eukaryotic gene expression," Nature, Nature, vol. 422(6932), pages 633-637, April.
    2. Duan, Wei-Long & Long, Fei & Li, Chun, 2014. "Reverse resonance and stochastic resonance in intracellular calcium oscillations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 52-57.
    3. M. Gosak & M. Marhl & M. Perc, 2008. "Chaos out of internal noise in the collective dynamics of diffusively coupled cells," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 62(2), pages 171-177, March.
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