A novel methodology for finding the regulation on gene expression data

被引：2

作者：

Liu, Wei ^{[1
]}

Wang, Bo ^{[1
]}

Glassey, Jarka ^{[2
]}

Martin, Elaine ^{[2
]}

Zhao, Jian ^{[1
]}

机构：

[1] Xi An Jiao Tong Univ, Sch Life Sci & Technol, Minist Educ, Key Lab Biomed Informat Engn, Xian 710049, Peoples R China

[2] Newcastle Univ, Sch Chem Engn & Adv Mat, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England

来源：

PROGRESS IN NATURAL SCIENCE-MATERIALS INTERNATIONAL | 2009年 / 19卷 / 02期

关键词：

Classifier design; Discriminant analysis; Gene expression data; Rand calculation;

D O I：

10.1016/j.pnsc.2008.07.003

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

DNA microarray technology is a high throughput and parallel technique for genomic investigation due to its advantages of simultaneously surveying features of large scales complex data in biology. This paper aims to find feature subset to build the classifier for gene expression data analysis. At first, K-means clustering algorithm was carried out on the dataset of yeast cell cycle. Based on Rand calculation, a statistical method was used to pick out the data points ( genes) for classifier design. Meanwhile, the principal component analysis was applied to help to construct the classifier. For the validation of classifier built and prediction of a target subset of genes, discriminant analysis in terms of partial least square regression and artificial neural network were also performed. (C) 2008 National Natural Science Foundation of China and Chinese Academy of Sciences. Published by Elsevier Limited and Science in China Press. All rights reserved.

引用

页码：267 / 272

页数：6

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