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The correlation of gene expression and co-regulated gene patterns in characteristic KEGG pathways by Lin Hua; Dong-guo Li; Hui Lin; Lin Li; Xia Li; Zhi-cheng Liu is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

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There is great interest in chromosome-and pathway-based techniques for genomics data analysis in the current work in order to understand the mechanism of disease. However, there are few studies addressing the abilities of machine learning methods in incorporating pathway information for analyzing microarray data. In this paper, we identified the characteristic pathways by combining the classification error rates of out-of-bag (OOB) in random forests with pathways information. At each characteristic pathway, the correlation of gene expression was studied and the co-regulated gene patterns in different biological conditions were mined by Mining Attribute Profile (MAP) algorithm. The discovered co-regulated gene patterns were clustered by the average-linkage hierarchical clustering technique. The results showed that the expression of genes at the same characteristic pathway were approximate. Furthermore, two characteristic pathways were discovered to present co-regulated gene patterns in which one contained 108 patterns and the other contained one pattern. The results of cluster analysis showed that the smallest similarity coefficient of clusters was more than 0.623, which indicated t

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Author

Lin Hua; Dong-guo Li; Hui Lin; Lin Li; Xia Li; Zhi-cheng Liu

Publisher

Elsevier Science; Elsevier ; Elsevier Inc.; Elsevier BV (ISSN 0022-5193)

Published

2010

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)