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首页> 外文期刊>Chaos, Solitons and Fractals: Applications in Science and Engineering: An Interdisciplinary Journal of Nonlinear Science >In the search for the low-complexity sequences in prokaryotic and eukaryotic genomes: how to derive a coherent picture from global and local entropy measures
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In the search for the low-complexity sequences in prokaryotic and eukaryotic genomes: how to derive a coherent picture from global and local entropy measures

机译:在寻找原核和真核基因组中的低复杂性序列中:如何从全局和局部熵测度中获得一致的图像

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We investigate on a possible way to connect the presence of low-complexity sequences (LCS) in DNA genomes and the non-stationary properties of base correlations. Under the hypothesis that these variations signal a change in the DNA function, we use a new technique, called non-stationarity entropic index (NSEI) method, and we prove that this technique is an efficient way to detect functional changes with respect to a random baseline. The remarkable aspect is that NSEI does not imply any training data or fitting parameter, the only arbitrarity being the choice of a marker in the sequence. We make this choice on the basis of biological information about LCS distributions in genomes. We show that there exists a correlation between changing the amount in LCS and the ratio of long- to short-range correlation. (C) 2003 Elsevier Ltd. All rights reserved.
机译:我们研究了一种可能的方法,以连接DNA基因组中低复杂度序列(LCS)的存在与碱基相关性的非平稳性质。在这些变化表明DNA功能发生变化的假设下,我们使用了一种称为非平稳熵指数(NSEI)方法的新技术,并且我们证明了该技术是检测随机变量功能变化的有效方法。基线。显着的方面是NSEI并不暗示任何训练数据或拟合参数,唯一的任意性是序列中标记的选择。我们根据有关基因组中LCS分布的生物学信息做出选择。我们表明,改变LCS中的数量和长短程相关比率之间存在相关性。 (C)2003 Elsevier Ltd.保留所有权利。

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