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.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0729111-155816 |
| Date | 29 July 2011 |
| Creators | Jan, Yi-An |
| Contributors | Mei-Hui Guo, May-Ru Chen, Shih-Feng Huang, Mong-Na Lo Huang, Fu-Chuen Chang |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0729111-155816 |
| Rights | user_define, Copyright information available at source archive |
Page generated in 0.0021 seconds