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Model-Based Clustering for Gene Expression and Change Patterns

It is important to study gene expression and change patterns over a time period because biologically related gene groups are likely to share similar patterns. In this study, similar gene expression and change patterns are found via model-based clustering method. Fourier and wavelet coefficients of gene expression data are used as the clustering variables. A two-stage model-based method is proposed for stepwise clustering of expression and change patterns. Simulation study is performed to investigate the effectiveness of the proposed methodology. Yeast cell cycle data are analyzed.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0729111-155816
Date29 July 2011
CreatorsJan, Yi-An
ContributorsMei-Hui Guo, May-Ru Chen, Shih-Feng Huang, Mong-Na Lo Huang, Fu-Chuen Chang
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0729111-155816
Rightsuser_define, Copyright information available at source archive

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