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http://dx.doi.org/10.5351/KJAS.2006.19.1.013

A Review of Cluster Analysis for Time Course Microarray Data  

Sohn In-Suk (Department of Statistics, Korea University)
Lee Jae-Won (Department of Statistics, Korea University)
Kim Seo-Young (Researcher, Research Institute for Basic Science, Chonnam National University)
Publication Information
The Korean Journal of Applied Statistics / v.19, no.1, 2006 , pp. 13-32 More about this Journal
Abstract
Biologists are attempting to group genes based on the temporal pattern of gene expression levels. So far, a number of methods have been proposed for clustering microarray data. However, the results of clustering depends on the genes selection, therefore the gene selection with significant expression difference is also very important to cluster for microarray data. Thus, this paper present the results of broad comparative studies to time course microarray data by considering methods of gene selection, clustering and cluster validation.
Keywords
Time course microarray data; Gene selection; Cluster analysis; Cluster validation;
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