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http://dx.doi.org/10.5351/CKSS.2005.12.2.335

Consensus Clustering for Time Course Gene Expression Microarray Data  

Kim, Seo-Young (Research Institute for Basic Science, Chonnam National University)
Bae, Jong-Sung (Department of Statistics, Chonnam National University)
Publication Information
Communications for Statistical Applications and Methods / v.12, no.2, 2005 , pp. 335-348 More about this Journal
Abstract
The rapid development of microarray technologies enabled the monitoring of expression levels of thousands of genes simultaneously. Recently, the time course gene expression data are often measured to study dynamic biological systems and gene regulatory networks. For the data, biologists are attempting to group genes based on the temporal pattern of their expression levels. We apply the consensus clustering algorithm to a time course gene expression data in order to infer statistically meaningful information from the measurements. We evaluate each of consensus clustering and existing clustering methods with various validation measures. In this paper, we consider hierarchical clustering and Diana of existing methods, and consensus clustering with hierarchical clustering, Diana and mixed hierachical and Diana methods and evaluate their performances on a real micro array data set and two simulated data sets.
Keywords
Consensus clustering; Time course gene expression data; Validation measures;
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