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Discovering Patterns of DNA Methylation: Rule Mining with Rough Sets and Decision Trees, and Comethylation Analysis

机译:DNA甲基化的发现模式:使用粗糙集和决策树进行规则挖掘以及共甲基化分析

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摘要

DNA methylation regulates the transcription of genes without changing their coding sequences. It plays a vital role in the process of embryogenesis and tumorgenesis. To gain more insights into how such epigenetic mechanism works in the human cells, we apply the two popular data mining techniques, i.e., Rough Sets, and Decision Trees, to uncover the logical rules of DNA methylation. Our results show that the Rough Sets method can generate and utilize fewer rules to fully separate the methylation dataset, whereas Decision Trees method relies on more rules but involves fewer decision variables to do the same task. We also find that some of the gene promoters are highly comethylated, demonstrating the evidence that genes are highly interactive epigenetically in human cells.
机译:DNA甲基化调节基因的转录而不改变其编码序列。它在胚胎发生和肿瘤发生过程中起着至关重要的作用。为了深入了解这种表观遗传机制如何在人类细胞中发挥作用,我们应用了两种流行的数据挖掘技术(即粗糙集和决策树)来揭示DNA甲基化的逻辑规则。我们的结果表明,粗糙集方法可以生成和利用更少的规则来完全分离甲基化数据集,而决策树方法则依赖于更多的规则,但是涉及更少的决策变量来完成相同的任务。我们还发现,某些基因启动子是高度共甲基化的,这证明了基因在人类细胞中是表观遗传学上高度相互作用的证据。

著录项

  • 来源
  • 会议地点 Kolkata(IN);Kolkata(IN)
  • 作者单位

    Department of Computer Science and Engineering, Hong Kong University of Science Technology, Hong Kong, China;

    Department of Computer Science and Engineering, Hong Kong University of Science Technology, Hong Kong, China;

    Institute for Infocomm Research, Singapore;

    Department of Computing, Hong Kong Polytechnic University, Hong Kong, China;

    Indian Statistical Institute, Kolkata, India;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 计算机网络;
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