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Title of Journal: Comput Stat

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Abbravation: Computational Statistics

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Springer-Verlag

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10.1007/s00417-009-1275-3

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1613-9658

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Bayesian modelbased tight clustering for time cou

Authors: Yongsung Joo George Casella James Hobert
Publish Date: 2009/06/16
Volume: 25, Issue: 1, Pages: 17-38
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Abstract

Cluster analysis has been widely used to explore thousands of gene expressions from microarray analysis and identify a small number of similar genes objects for further detailed biological investigation However most clustering algorithms tend to identify loose clusters with too many genes In this paper we propose a Bayesian tight clustering method for time course gene expression data which selects a small number of closelyrelated genes and constructs tight clusters only with these closelyrelated genes

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