Steady-state analysis of genetic regulatory networks modeled by nonlinear ordinary differential equations

机译：用非线性常微分方程建模的遗传调控网络的稳态分析

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Although Ordinary Differential Equations (ODEs) have been used to model Genetic Regulatory Networks (GRNs) in many previous works, their steady-state behaviors are not well studied. However, a phenotype corresponds to a steady-state gene expression pattern and steady-state analysis of GRNs can provide valuable information on the stability of the GRNs, insights into cellular regulatory mechanisms underlying disease development as well as possible interventions for disease control. In this study, the steady-state behaviors of the nonlinear GRN models are analyzed based on time series data. The steady-state solutions and stability of nonlinear GRNs including polynomial model, sigmoidal model and S-system model are discussed in details.

机译：尽管在许多先前的工作中已经使用常微分方程（ODE）来对遗传调控网络（GRN）进行建模，但是对它们的稳态行为却没有进行很好的研究。然而，表型对应于稳态基因表达模式，对GRN的稳态分析可以提供有关GRN稳定性，对疾病发展基础的细胞调节机制的深入了解以及对疾病控制的可能干预措施的有价值的信息。在这项研究中，基于时间序列数据分析了非线性GRN模型的稳态行为。详细讨论了包括多项式模型，S形模型和S-系统模型在内的非线性GRN的稳态解和稳定性。

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《Computational Intelligence in Bioinformatics and Computational Biology, 2009. CIBCB '09》|2009年|182-185|共4页
会议地点 Nashville TN(US);Nashville TN(US)
作者
Haixin Wang; Lijun Qian; Dougherty E.R.;
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Dept. of Math. Comput. Sci., Fort Valley State Univ., Fort Valley, GA;

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cellular biophysics; diseases; genetics; molecular biophysics; nonlinear differential equations; S-system model; cellular regulatory mechanisms; disease control; disease development; genetic regulatory networks; nonlinear ordinary differential equation; sigmoidal model; steady-state GRN analysis; steady-state gene expression pattern;

机译：细胞生物物理学;疾病;遗传学;分子生物物理学;非线性微分方程; S系统模型;细胞调控机制;疾病控制;疾病发展;遗传调控网络;非线性常微分方程; S型模型;稳态GRN分析;稳态基因表达模式;

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1. Disturbance Analysis of Nonlinear Differential Equation Models of Genetic SUM Regulatory Networks [J] . Li Ping, Lam James Computational Biology and Bioinformatics, IEEE/ACM Transactions on . 2011,第1期

机译：遗传SUM调节网络非线性微分方程模型的扰动分析。
2. Inference of Noisy Nonlinear Differential Equation Models for Gene Regulatory Networks Using Genetic Programming and Kalman Filtering [J] . Qian L., Wang H., Dougherty E. R. IEEE Transactions on Signal Processing . 2008,第7期

机译：基于遗传规划和卡尔曼滤波的基因调控网络噪声非线性微分方程模型的推论
3. Stability and Flexibility from a System Analysis of Gene Regulatory Networks Based on Ordinary Differential Equations [J] . Mika Gustafsson, Michael Hornquist The Open Bioinformatics Journal . 2011,第1期

机译：基于常微分方程的基因调控网络系统分析的稳定性和灵活性
4. Steady-state Analysis of Genetic Regulatory Networks Modeled by Nonlinear Ordinary Differential Equations [C] . Haixin Wang, Lijun Qian, Edward R. Dougherty IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology . 2009

机译：非线性常微分方程建模的遗传调节网络稳态分析
5. Theta methods for nonlinear ordinary differential equations and error analysis [D] . Walker, Matthew 2014

机译：非线性常微分方程的Theta方法和误差分析
6. Modeling Genome-Wide Dynamic Regulatory Network in Mouse Lungs with Influenza Infection Using High-Dimensional Ordinary Differential Equations [O] . Shuang Wu, Zhi-Ping Liu, Xing Qiu, -1

机译：使用高维常微分方程对具有流感感染的小鼠肺进行全基因组动态调节网络建模
7. Steady-state Analysis of Genetic Regulatory Networks Modeled by Nonlinear Ordinary Differential Equations [O] . Haixin Wang, Lijun Qian, Edward R. Dougherty 2014

机译：非线性常微分方程模型的遗传调控网络稳态分析

Steady-state analysis of genetic regulatory networks modeled by nonlinear ordinary differential equations

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