文献类型：期刊文献

英文题名：Gene selection of rat hepatocyte proliferation using adaptive sparse group lasso with weighted gene co-expression network analysis

作者：Li, Juntao[1];Wang, Yadi[2];Xiao, Huimin[3];Xu, Cunshuan[4]

第一作者：Li, Juntao

通讯作者：Wang, YD[1]

机构：[1]Henan Normal Univ, Sch Math & Informat Sci, Xinxiang 453007, Henan, Peoples R China;[2]Southeast Univ, Sch Comp Sci & Engn, Nanjing 211189, Jiangsu, Peoples R China;[3]Henan Univ Econ & Law, Dept Math & Informat Sci, Zhengzhou 450002, Henan, Peoples R China;[4]Henan Normal Univ, State Key Lab Cultivat Base Cell Differentiat Reg, Xinxiang 453007, Henan, Peoples R China

第一机构：Henan Normal Univ, Sch Math & Informat Sci, Xinxiang 453007, Henan, Peoples R China

通讯机构：[1]corresponding author), Southeast Univ, Sch Comp Sci & Engn, Nanjing 211189, Jiangsu, Peoples R China.

年份：2019

卷号：80

起止页码：364-373

外文期刊名：COMPUTATIONAL BIOLOGY AND CHEMISTRY

收录：;EI(收录号：20192006937188);Scopus(收录号：2-s2.0-85065653066);WOS:【SCI-EXPANDED(收录号:WOS:000474314000040)】；

基金：This work was supported by the Natural Science Foundation of China (61203293, 61702164, 31700858), Scientific and Technological Project of Henan Province (172102210047), and Foundation of Henan Educational Committee (18A520015, 19A520005).

语种：英文

外文关键词：Rat hepatocyte proliferation; Gene selection; Weighted gene co-expression network; Group lasso; Adaptive lasso

摘要：Grouped gene selection is the most important task for analyzing the microarray data of rat liver regeneration. Many existing gene selection methods cannot outstand the interactions among the selected genes. In the process of rat liver regeneration, one of the most important events involved in many biological processes is the proliferation of rat hepatocytes, so it can be used as a measure of the effectiveness of the method. Here we proposed an adaptive sparse group lasso to select genes in groups for rat hepatocyte proliferation. The weighted gene co expression networks analysis was used to identify modules corresponding to gene pathways, based on which a strategy of dividing genes into groups was proposed. A strategy of adaptive gene selection was also presented by assessing the gene significance and introducing the adaptive lasso penalty. Moreover, an improved blockwise descent algorithm was proposed. Experimental results demonstrated that the proposed method can improve the classification accuracy, and select less number of significant genes which act jointly in groups and have direct or indirect effects on rat hepatocyte proliferation. The effectiveness of the method was verified by the method of rat hepatocyte proliferation.