微陣列技術為了能夠處理大量的基因而廣泛的應用在生物及醫學上面，而致命疾病的基因是現代醫學家所想研究且探討的一個主題。本篇論文依據此動機法展一套迅速準確且有重複性的系統提供下面的功能：
１. 偵測正常人和癌症人表現量差異較大的基因
２. 選取能夠分辨兩種不同疾病基因的集合的方法
３. 把結果視覺化並列出基因的Accession Number
這篇論文我們用兩種不同的方法再做前背景的偵測分別是Otsu和Gaussian Mixture Model此外在正規化部分使用LOWESS演算法和Moving Average Filter 兩種方法實作。最後使用Fisher linear discriminant 方法找尋一組最能區別兩種疾病的基因並用K-means和Hierarchical等方式檢查可靠性。此外為了測試此方法之可行度　做了小樣本的分類測試，使用了Quadratic 和 3-NN演算法。

The microarray technology was born for dealing with a lot of genes. It is developed to reveal various genes related to fatal diseases what people want to discover. The purpose of this thesis is to implement a system for dealing with microarray image pattern analysis fast, accurately and repeatedly. And the system provides the following function:
(i) Detect differentially expressed genes.
(ii) Select a subset of genes which best distinguishes different diseases.
(iii) Visualizing our experimental results by the dendrograms.
In this thesis, we use two different methods, Otsu and GMM to do gene expression computation. And then we use LOWESS and Moving Average Filtering to do normalization. Finally, we use Fisher linear discriminant for finding differentially expressed genes and check the results by K-means and Hierarchical clustering.

[Bere2005] M. Berens, H. Liu, L. Parsons, L. Yu, and Z. Zhao. “Fostering biological relevance in feature selection for microarray data”, IEEE Intelligent Systems, Vol. 20, No. 6, 29-32, 2005.
[Cai2006] X. Cai and G.B. Giannakis, “Identifying Differentially Expressed Genes in Microarray Experiments With Model-Based Variance Estimation”, IEEE Transactions on signal processing, Vol. 54, No. 6, 2418-2426, 2006.
[Caus2003] H.C. Causton, J. Quackenbush, and A. Brazma, “Microarray Gene Expression Analysis”, Blackwell Publishing, 2003.
[Chen2007] T.S. Chen, Y.L. Chen, M.S. Liou, W.S. Hsu, C.C. Lin, and Y.H. Chiu, “A New Two-Phase Clustering Algorithm Based on K-means and Hierarchical Clustering with Single-Linkage Agglomerative Method”, Journal of Computers, Vol. 17, No. 1, 65-76, 2006.
[Chua2004] H.Y. Chuang, H.F. Liu, S. Brown, C. McMunn-Coffran, C.Y. Kao, and D.F. Hsu, “Identifying Significant Genes from Microarray Data”, Proceedings of Fourth IEEE Symposium on Bioinformatics and Bioengineering, 358-365, 2004.
[Clev1979] W.S. Cleveland, “Robust Locally Weighted Regression and Smoothing Scatterplots”, Journal of the American Statistical Association, No. 74, 829-836, 1979.
[Clev1988] W.S. Cleveland and S.J. Devlin, “Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting”, Journal of the American Statistical Association, Vol. 83, 596-610, 1988.

[Demp1977] A.P. Dempster, N.M. Laird, and D.B. Rubin, “Maximum likelihood from incompletedata via the EM algorithm”, Journal of the Royal Statistical Society, Vol. 39, 1-38, 1977.
[Dudo2001] R.O. Duda, P.E. Hart, and D.G. Stork, “Pattern Classification”, A Wiley-Interscience Publication, John Wiley & Sons, Inc., New York, 2001.
[Dudo2002] S. Dudoit, Y.H. Yang, M.J. Callow, and T.P. Speed, “Statistical Methods for Identifying Differentially Expressed Genes in Replicated cDNA Microarray Experiments”, Statistica Sinica, Vol. 12, 111-139, 2002.
[Ghos2002] D. Ghosh and A.M. Chinnaiyan, “Mixture modeling of gene expression data from Microarray experiments”, Bioinformatics, Vol. 18, No. 2, 275-286, 2002.
[Gonz2002] R.C. Gonzalez and R.E. Woods, “Digital Image Processing”, Prentice-Hall, Inc., 2002.
[Hans2005] D. Hanselman and B. Littlefield, “Mastering Matlab 7”, 2005.
[Hsie2005] Y.P. Hsieh, “Gene Discovery from Microarray Images”, M.S. Thesis, Department of Computer Science, NTHU, Taiwan, 2005.
[Otsu1979] N. Otsu, “A Threshold Selection Method from Gray-Level Histograms”, Journal of IEEE Transactions on Systems, Man, and Cybernetics, Vol. 9, No.1, 62-66, 1979.
[Ross2000] D.T. Ross, U. Scherf, M.B. Eisen, et al., ”Systematic variation in gene expression patterns in human cancer cell lines”, Journal of Nature Genetics, Vol. 24, No. 3, 227-235, 2000.
[Tsai2006] M.Y. Tsai, “Gene Expression Computation on Microarray Image Data”, M.S. Thesis, Department of Computer Science, NTHU, Taiwan, 2006.

[Yang2001] Y.H. Yang, S. Dudoit, P. Luu, and T.P. Speed, “Normalization for cDNA Microarray Data”, SPIE BIOS 2001, San Jose, California, 2001.
[Zach2008] E. Zacharia and D. Maroulis, “An Original Genetic Approach to the Fully Automatic Gridding of Microarray Images”, IEEE Transactions on Medical Imaging, Vol. 27, No. 6, 805-813, 2008.