基于相关性分析和主成分分析的基因调控网络研究  

Research on Gene Regulatory Network based on Correlation Analysis and Principal Component Analysis

作　　者：董艺 路云龙[1] DONG Yi;LU Yunlong(School of Mathematics and Statistics,Beihua University,Jilin 132013,China)

机构地区：[1]北华大学数学与统计学院,吉林吉林132013

出　　处：《吉林化工学院学报》2021年第9期112-116,共5页Journal of Jilin Institute of Chemical Technology

基　　金：大学生创新创业项目(201910201092)。

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.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.

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 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]