Responsive image
博碩士論文 etd-0729111-155816 詳細資訊
Title page for etd-0729111-155816
論文名稱
Title
基因表現與改變形態的模型分群法研究
Model-Based Clustering for Gene Expression and Change Patterns
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
45
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2011-06-23
繳交日期
Date of Submission
2011-07-29
關鍵字
Keywords
傅立葉係數、基因表現、模型分群法、小波係數、酵母菌細胞週期
Gene expression, Model-based clustering, Wavelet coefficients, Fourier coefficients, Yeast cell cycle data
統計
Statistics
本論文已被瀏覽 5827 次,被下載 5
The thesis/dissertation has been browsed 5827 times, has been downloaded 5 times.
中文摘要
生物上認為具有相關性的基因之間擁有相似的模式,所以研究細胞基因表現與改變型態為一個重要的議題。在本篇論文中,透過模型分群法,找出擁有相似表現與改變型態的基因。將觀測基因表現模式的數據,透過傅立葉轉換和小波轉換,所得的傅立葉係數和小波係數作為分群的變數。在本研究中提出兩階段的分群方法,對基因表現與改變型態分群,並透過模擬研究來比較兩種分群方法的效率性。在實證分析上,以酵母菌細胞週期的數據例,探討分群方法的可行性。
Abstract
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.
目次 Table of Contents
論文審定書i

謝誌ii

摘要iii

Abstract iv

1 Introduction 1

2 The Model and Orthogonal Transform 2
2.1 Fourier Transform 3
2.2 Wavelet Transform 7

3 Clustering methods 10
3.1 Model-based Agglomerative Hierarchical Clustering 10
3.1.1 Model-based Clustering 10
3.1.2 Model-based Agglomerative Hierarchical Clustering 11
3.1.3 Estimation of the Number of Clusters 11
3.2 K-means Clustering Method 13
3.3 The Clustering Strategies 13
3.3.1 One-stage Method 14
3.3.2 Two-stage Method 15
3.3.3 Two-stage(A) Method 15

4 The Cell Cycle and Saccharomyces Cerevisiae Data 15

5 Simulation Study 17
5.1 Comparison with Kim and Kim (2008) 17
5.2 Simulation with Yeast Cell Cycle Data 19

6 Conclusion 21

References 23

Appendix 24
A.1 Tables 24
A.2 Figures 31
參考文獻 References
[1] Banfeild, J. D. and Raftery, A. E. (1993). Model-Based Gaussian and Non-Gaussian
Clustering. Biometrics, 49, 803-821.
[2] Fraley, C. (1998). Algorithms for model-based Gaussian hierarchical clustering. SIAM
Journal on Scienti‾c Computing, 20, 270-281.
[3] Fraley, C. and Raftery, A. E. (2006). MCLUST Version 3 for R: Normal Mixture Mod-
eling and Model-Based Clustering. Technical Report no. 504, Department of Statistics,
University of Washington.
[4] Kim, J. and Kim, H. (2008). Clustering of Change Patterns Using Fourier Coefficients.
Bioinformatics, 24, 184-191.
[5] Percival, D. B. and Walden, A. T. (2000). Wavelet Methods for Time Series Analysis.
Cambridge University Press, Cambridge.
[6] Scott, A. J. and Symons, M. J. (1971). Clustering methods based on likelihood ratio
criteria. Biometrics, 27, 387-397.
[7] Wei, W.S. (2006). Time series analysis : univariate and multivariate methods, 2nd
Edition. Pearson Addison Wesley, Boston.
電子全文 Fulltext
本電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。
論文使用權限 Thesis access permission:自定論文開放時間 user define
開放時間 Available:
校內 Campus: 已公開 available
校外 Off-campus:永不公開 not available

您的 IP(校外) 位址是 44.201.59.20
論文開放下載的時間是 校外不公開

Your IP address is 44.201.59.20
This thesis will be available to you on Indicate off-campus access is not available.

紙本論文 Printed copies
紙本論文的公開資訊在102學年度以後相對較為完整。如果需要查詢101學年度以前的紙本論文公開資訊,請聯繫圖資處紙本論文服務櫃台。如有不便之處敬請見諒。
開放時間 available 已公開 available

QR Code