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Quantitative Models for Statistical Nucleosome Occupancy Prediction

机译：统计核微核心预测的定量模型

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摘要

Nucleosome is the basic unit of DNA in eukaryotic cells. As nucleosomes limit the accessibility of the wrapped DNA to transcription factors and other DNA-binding proteins, their positions play an essential role in regulations of gene activities. Experiments have indicated that DNA sequence strongly influences nucleosome positioning by enhancing or reducing their binding affinity to nucleosomes, therefore providing an intrinsic cell regulatory mechanism. While some sequence features are known to be nucleosome forming or nucleosome inhibiting, however, existing models have limited accuracy in predicting quantitatively nucleosomes occupancy (i.e., statistical nucleosome positioning) based on DNA sequence. In this paper, we propose new quantitative models for DNA sequence-based nucleosome-occupancy prediction based on dinucleotide-matching features, where the parameters are learned through regression algorithms. Experimental results on a genome-wide set of yeast dataset show that our models give more accurate predictions than existing models.
机译：核小体是真核细胞中DNA的基本单位。由于核体限制包裹的DNA与转录因子和其他DNA结合蛋白的可用性，它们的立场在基因活性的规定中起重要作用。实验表明，DNA序列通过增强或降低对核体的增强或降低它们的结合亲和力来强烈影响核心体定位，因此提供了内在细胞调节机制。然而，虽然已知一些序列特征是核体形成或核小体抑制的虽然，现有模型在基于DNA序列预测定量核体占据（即统计核小体定位）的准确性有限。在本文中，我们提出了基于二核苷酸匹配特征的DNA序列的核心占用预测的新定量模型，其中通过回归算法学习参数。关于基因组型酵母数据集的实验结果表明，我们的模型提供比现有模型更准确的预测。

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