非高斯噪声与高斯色噪声作用的基因调控网络研究
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摘要
研究非高斯噪声与高斯色噪声激励下的Myc/E2F/MiR-17-92网络模型,通过求解相应的Fokker-Planck-Kolmogorov方程,得到了系统的稳态概率密度函数。同时,从理论上讨论了非高斯噪声强度、偏离高斯噪声程度以及两噪声的互相关强度对稳态概率密度分布的影响,发现非高斯噪声强度、偏离高斯噪声程度以及噪声间的互相关强度在一定条件下不仅能够影响基因转录的效率,还能使基因转录在低浓度稳态和高浓度稳态间转换。
In this paper,the stationary probability distribution of an abstract model on the Myc/E2 F/MiR17-92 network presented by BALTAZAR D A et al with coupling non-Gaussian noise and Gaussian colored noise was investigated.By solving the corresponding Fokker-PlanckKolmogorov equation,we theoretically discussed how the non-Gaussian noise intensity,departure from the Gaussian noise,and the cross-correlation intensity between non-Gaussian noise and Gaussian colored noise impact stationary probability distribution.The results demonstrate that gene transcription efficiency and toggle switch process can be influenced by non-Gaussian noise intensity,departure from the Gaussian noise,or the cross-correlation intensity between nonGaussian noise and Gaussian colored noise.
In this paper,the stationary probability distribution of an abstract model on the Myc/E2 F/MiR17-92 network presented by BALTAZAR D A et al with coupling non-Gaussian noise and Gaussian colored noise was investigated.By solving the corresponding Fokker-PlanckKolmogorov equation,we theoretically discussed how the non-Gaussian noise intensity,departure from the Gaussian noise,and the cross-correlation intensity between non-Gaussian noise and Gaussian colored noise impact stationary probability distribution.The results demonstrate that gene transcription efficiency and toggle switch process can be influenced by non-Gaussian noise intensity,departure from the Gaussian noise,or the cross-correlation intensity between nonGaussian noise and Gaussian colored noise.
引文
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[2]HAN R F,HUANG G Q,WANG Y J,et al.Increased gene expression noise in human cancers is correlated with low p53and immune activities as well as late stage cancer[J].Oncotarget,2016,44(7).
[3]BALTAZAR D A,KIM Y,MELISSA G,et al.MicroRNA regulation of a cancer network:consequences of the feedback loops involving miR-17-92,E2F,and Myc[J].PNAS,2008,105(50):19678-19683.
[4]LI Y C,LI Y M,ZHANG H,et al.MicroRNA-mediated positive feedback loop and optimized bistable switch in a cancer network involving miR-17-92[J].PloS ONE,2011,6(10):e26302.
[5]ZHANG H,CHEN Y L,CHEN Y.Noise propagation in gene regulation networks involving interlinked positive and negative feedback loops[J].PloS ONE,2012,7(12):e51840.
[6]ZHANG C,DU L P,WANG T H,et al.Impact of time delay in a stochastic gene regulation network[J].Chaos Solitions&Fractals,2017,96:120-129
[7]FUENTES M,TORAL R,WIO H S.Enhancement of stochastic resonance:the role of non-Gaussian noises[J].Physica A,2001,295(1):114-122.
[8]FUENTES M,WIO H S,TORAL R.Effective Markovian approximation for non-Gaussian noises:apath integral approach[J].Physica A,2002,303(1):91-104.
[9]WIO H S,TORAL R.Effect of non-Gaussian noise sources in a noise-induced transition[J].Physica D,2004,193(1):161-168.
[10]GUO Q,SUN Z K,XU W.The properties of the anti-tumor model with coupling non-Gaussian noise and Gaussian colored noise[J].Physica A,2016,449(c):43-52.
[11]SANCHO J M,MIGUEL M S,KATZ S L,et al.Analytical and numerical studies of multiplicative noise[J].Physical Review A,1982,26(3):1589-1609.
[12]JIA Y,LI J R.Stochastic system with colored correlation between white noise and colored noise[J].Physica A,1998,252(3/4):417-427.
[13]LIANG G Y,CAO L,WU D J.Approximate Fokker-Planck equation of system driven by multiplicative colored noises with colored cross-correlation[J].Physica A,2004,335(3):371-384.
[14]ZHANG H Q,XU W,XU Y.The study on a stochastic system with non-Gaussian noise and Gaussian colored noise[J].Physica A,2009,388(6):781-788.