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Computational discovery of feature patterns in nucleosomal DNA sequences

机译:核小体DNA序列中特征模式的计算发现

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The identification of important factors that affect nucleosome formation is critical to clarify nucleosome-forming mechanisms and the role of the nucleosome in gene regulation. Various features reported in the literature led to our hypothesis that multiple features can together contribute to nucleosome formation. Therefore, we compiled 779 features and developed a pattern discovery and scoring algorithm FFN (Finding Features for Nucleosomes) to identify feature patterns that are differentially enriched in nucleosome-forming sequences and nucleosome-depletion sequences. Applying FFN to genome-wide nucleosome occupancy data in yeast and human, we identified statistically significant feature patterns that may influence nucleosome formation, many of which are common to the two species. We found that both sequence and structural features are important in nucleosome occupancy prediction. We discovered that, even for the same feature combinations, variations in feature values may lead to differences in predictive power. We demonstrated that the identified feature patterns could be used to assist nucleosomal sequence prediction. (C) 2014 Elsevier Inc. All rights reserved.
机译:鉴定影响核小体形成的重要因素对于阐明核小体形成机制和核小体在基因调控中的作用至关重要。文献中报道的各种特征导致我们的假设,即多种特征可以共同促进核小体的形成。因此,我们编辑了779个特征,并开发了模式发现和评分算法FFN(核小体的发现特征)以识别在核小体形成序列和核小体耗尽序列中差异性富集的特征模式。将FFN应用于酵母和人类中全基因组的核小体占用数据,我们确定了可能影响核小体形成的统计学上显着的特征模式,这两个物种中有许多是共有的。我们发现,序列和结构特征在核小体占用预测中都很重要。我们发现,即使对于相同的特征组合,特征值的变化也可能导致预测能力的差异。我们证明了已识别的特征模式可用于辅助核小体序列预测。 (C)2014 Elsevier Inc.保留所有权利。

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