基于相关性分析和主成分分析的基因调控网络研究

doi:10.16039/j.cnki.cn22-1249.2021.09.021

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摘要

为了构建基因调控网络模型，提出了相关性分析和主成分分析相结合的方法。利用皮尔逊相关系数进行相关性分析，构造初始的基因调控网络。进而利用主成分分析法确立剪边原则，从而获得新的基因调控网络。采用Dream3中的大肠杆菌（Ecoli1）10个基因的表达数据进行测试，结果表明，参考黄金标准下的基准网络，所提方法获得的基因调控网络具有较高的准确性。

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	董艺
	路云龙

关键词: 基因调控网络主成分分析相关性分析皮尔逊相关系数

Abstract:

In order to construct a gene regulatory network model, a method combining correlation analysis and principal component analysis is proposed. Use Pearson's correlation coefficient for correlation analysis to construct an initial gene regulatory network. Then use the principal component analysis method to establish the trimming principle, so as to obtain a new gene regulatory network. Using the expression data of 10 genes of Escherichia coli (Ecoli1) in Dream3 for testing, the results show that referring to the benchmark network under the gold standard, the gene regulation network obtained by the proposed method has high accuracy.

Key words: gene regulatory network principal component analysis correlation analysis Pearson correlation coefficient

出版日期: 2021-09-25 发布日期: 2021-09-25 整期出版日期: 2021-09-25

TP391

引用本文:

董艺, 路云龙. 基于相关性分析和主成分分析的基因调控网络研究 [J]. 吉林化工学院学报, 2021, 38(9): 112-116.
DONG Yi, LU Yunlong. Research on Gene Regulatory Network Based on Correlation Analysis and Principal Component Analysis . Journal of Jilin Institute of Chemical Technology, 2021, 38(9): 112-116.

链接本文:

https://xuebao.jlict.edu.cn/CN/10.16039/j.cnki.cn22-1249.2021.09.021 或 https://xuebao.jlict.edu.cn/CN/Y2021/V38/I9/112

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