基因调控网络

  • 网络Gene regulatory network
基因调控网络基因调控网络
  1. 基于DNA损伤的p53基因调控网络模型研究

    The Model Study of P53 Gene Regulatory Networks under DNA damage

  2. miRNA参与p53基因调控网络研究进展

    Research progress of miRNA involved in p53 gene regulatory networks

  3. 基于改进PSO的基因调控网络重构方法

    Reconstruction Method of Gene Regulatory Network Based on Modified Particle Swarm Optimization

  4. 用FCM聚类和非参数回归方法推断基因调控网络

    Inference of Gene Regulatory Network Using FCM Clustering and Nonparametric Regression Algorithm

  5. 近年来,科学家发现复杂的基因调控网络是构建在结构简单的motif之上的。

    Recently , scientists find that complex genetic regulatory network is actually consisted of simple building blocks-Motif .

  6. 研究人员还开发一种期望最大化基因调控网络的建模(EM)的时间序列,从基因表达数据的算法。

    The authors also develop an expectation – maximization ( EM ) algorithm for modeling gene regulatory networks from gene expression time series data .

  7. 由于基因调控网络中生物化学反应的时间多尺度性,如DNA与蛋白质结合以及蛋白质聚合等快速反应、转录翻译和降解等慢速反应,延滞现象在基因调控网络中普遍存在。

    Time delay kinetics are ubiquitous in gene regulation , because of the vast separation of time scales between the fast reactions like DNA-binding and dimerizations , and slow reactions like translation , transcription and degradation .

  8. 利用自由权值矩阵和LMI方法,首先得到了几个时滞区间相关和时滞导数相关/无关的时滞基因调控网络的全局渐近稳定判定条件。

    First , by employing some free-weighting matrices and linear matrix inequalities , new delay-range-dependent and delay-derivative-dependent / independent stability criteria are derived .

  9. 平面问题在印制电路板的设计和大规模集成电路(VLSI)的布线方面有着重要的应用,对于很多可视化问题,例如基因调控网络的可视化也有着重大的意义。

    It is widely used in designing printed circuit boards , routing very-large-scale integration ( VLSI ) circuits and very important to the visibility of the Gene Regulatory Network .

  10. 基于多源数据融合的变结构DBN模型基因调控网络构建

    Inferring Gene Regulatory Network Based on Structure Varied Dynamic Bayesian Network and Multi-Source Fusion

  11. 熟悉了解转录因子DNA结合的参数选择,不仅会有效洞察DNA的识别机制,同时允许更准确地预测基因组调控元件,这些元件是理解细胞基因调控网络的一个主要障碍。

    Understanding the evolution of TF DNA-binding preferences will not only provide useful insights on the mechanism of DNA recognition , it will also allow more accurate prediction of genomic regulatory elements , which still constitutes a major hurdle in understanding cellular gene regulatory networks .

  12. 基于此,本文主要做了以下工作:1、对具有时变时滞的基因调控网络,在存在外部噪声扰动的情况下,采用自适应滤波的方法设计自适应律,通过构造Lyapunov函数判断系统的随机稳定性。

    The main results of the thesis are as follows : 1 . For genetic regulatory networks with time-varying delays and uncertain noise disturbances , some adaptive laws are derived by using adaptive filtering approach and to ensure the stochastic stability by constructing Lyapunov functional .

  13. 通过研究不同条件下基因调控网络的Derrida曲线,我们发现正常细胞更加接近于混沌的边缘,这验证了Kauffman提出的混沌边缘假说。

    Through the study of the Derrida curve under different conditions , we found that the normal cell is closer to the edge of chaos , which supports the hypothesis of Kauffman .

  14. 本研究通过cDNA阵列的方法,从巴西橡胶树低温cDNA文库中筛选橡胶冷应答基因调控网络中的一些抗寒相关基因,分析其功能及各个基因之间的相互关系。

    In this research , we used the method of cDNA array to screen the genes response the cold stress from the cDNA library of rubber tree . The relationship of these genes and its function were analyzed . The main results were summarized as follows : 1 .

  15. 利用Bernoulli随机分布,研究了带有随机离散时滞和分布时滞基因调控网络的随机稳定性问题。相比较现有文献而言,在基因的翻译和反馈调控过程中都存在离散随机时滞和分布时滞。

    Based on Bernoulli stochastic vari - ables , we investigate the delay-probability-distribution-dependent stability problem of stochastic genetic regulatory networks with random discrete time delays and distributed time delays , which exist , in both translation process and feedback regulation process .

  16. 基因调控网络是生物动态系统,它的基本特征是稳定性,具有重要的研究意义。本文考虑基因调控网络的非线性、时滞、随机干扰等特点,建立具有Lurie系统形式的连续时间基因调控网络模型。

    GRNs are biochemical dynamical systems , and their basic feature is stability , which is of great research significance . A continuous-time GRNs model is proposed by considering nonlinear , time delay and stochastic perturbation , which has a form of Lurie system .

  17. 复杂基因调控网络常呈现出非线性动力学行为。

    Complex gene regulatory networks often show some nonlinear dynamical behavior .

  18. 使用稳态系统和粒群优化算法进行基因调控网络推断

    Gene regulatory networks inference with S-system model and particle swarm optimization

  19. 目的讨论利用模糊相关系数建立基因调控网络。

    Objective To construct the gene network by Fuzzy correlation matrix .

  20. 酵母基因调控网络的微分方程模型研究

    Study on Regulatory Network of Yeast Genes by Differential Equations Model

  21. 基因调控网络的系统生物学建模

    Modeling of the Gene Regulation Network with a Systems Biology Approach

  22. 一种改进的多元回归估计基因调控网络的方法

    An Improved Multiple Regression Analysis for Estimating Gene Regulatory Network

  23. 常微分方程系统是研究基因调控网络的常用工具之一。

    Ordinary differential equation system is one of powerful tools for GRN .

  24. 从酵母表达时间序列估计基因调控网络

    Estimating Coarse Gene Networks from Yeast Gene Expression Time Series

  25. 基于微分方程模型的基因调控网络初步研究

    The Preliminary Research Based on Differential Equation Model of Genetic Regulatory Network

  26. 目的寻求一种新的描述基因调控网络的微分方程模型。

    Objective To explore a new differential equation to describe gene regulatory network .

  27. 基因调控网络内涨落性质的理论研究

    Theoretical Investigation of Intrinsic Fluctuation in Gene Regulation Network

  28. 基于线性回归模型的基因调控网络重构算法的研究

    Research on the Gene Regulatory Network Reconstruction Algorithm Based on Linear Regression Model

  29. 一种新颖的基因调控网络结构学习方法

    Novel structure learning method for constructing gene regulatory network

  30. 肝癌基因调控网络构建方法与系统分析。

    Construction and systems biology analysis of gene regulatory network in liver cancer .