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具有关键位置集和核小体亲和力的核小体定位

Nucleosome Positioning with Set of Key Positions and Nucleosome Affinity.

作者信息

Wang Jia, Liu Shuai, Fu Weina

机构信息

Experimental Instrument Center, Dalian Polytechnic University, Dalian, Liaoning, 116034, China.

College of Computer Science, Inner Mongolia University, Hohhot, Inner Mongolia, 010012, China ; School of Physical Science and Technology, Inner Mongolia University, Inner Mongolia, 010012, China.

出版信息

Open Biomed Eng J. 2014 Dec 31;8:166-70. doi: 10.2174/1874120701408010166. eCollection 2014.

Abstract

The formation and precise positioning of nucleosome in chromatin occupies a very important role of study in life process. Today, many researchers discover that the positioning where the location of a DNA sequence fragment wraps around a histone in genome is not random but regular. However, the positioning is closely relevant to the concrete sequence of core DNA. So in this paper, we analyzed the relation between the affinity and sequence structure of core DNA sequence, and extracted the set of key positions. In these positions, the nucleotide sequences probably occupied mainly action in the binding. First, we simplified and formatted the experimental data by the affinity. Then, to find the key positions in the wrapping, we used neural network to analyze the positive and negative effect of nucleosome generation for every position in core DNA sequences. However, we reached a class of weights with every position to describe this effect. Finally, based on the positions with high weights, we analyzed the reason why the chosen positions are key positions, and used these positions to construct a model of nucleosome positioning predict. Experimental results show the effectiveness of our method.

摘要

核小体在染色质中的形成及精确定位在生命过程研究中占据着非常重要的地位。如今,许多研究人员发现,基因组中DNA序列片段围绕组蛋白缠绕的位置并非随机,而是具有规律性。然而,这种定位与核心DNA的具体序列密切相关。因此,在本文中,我们分析了核心DNA序列的亲和力与序列结构之间的关系,并提取了关键位置集。在这些位置上,核苷酸序列可能在结合中起主要作用。首先,我们根据亲和力对实验数据进行简化和格式化。然后,为了找到缠绕中的关键位置,我们使用神经网络分析核心DNA序列中每个位置对核小体生成的正负效应。然而,我们得到了一类权重来描述每个位置的这种效应。最后,基于高权重位置,我们分析了所选位置成为关键位置的原因,并利用这些位置构建了一个核小体定位预测模型。实验结果表明了我们方法的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7e4f/4549903/b4d23cd89c87/TOBEJ-8-166_F1.jpg

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