臺灣博碩士論文加值系統

中心顆粒體主要是在細胞週期有絲分裂後期產生的短暫胞器，其結構是由多種蛋白質緊密結合而成。若中心顆粒體無法順利形成或正確受調控，則將導致細胞質分裂末期無法完成，進而產生多核的細胞形態，此為癌細胞的重要生成原因之一。本研究探討人類中間體基因利用同源性關係對應出酵母菌基因及文獻中的相關酵母菌基因，總共為60個酵母菌基因。利用網路成份分析法(Network Component Analysis, NCA)，藉由不同的挑選基因方式，分析特定轉錄因子(Transcription Factor)對於酵母菌基因的調控關係及各個轉錄因子的活性表現的是否有差異性，其中在轉錄因子活性表現上與Tsai[1]所使用的統計方式分析結果大致是相同的。接著各別分析Spellman[2]所提供的alpha、cdc15、cdc28、elu四種實驗的微陣列矩陣，經由分析得到結果，討論其轉錄因子在細胞週期中的活性表現與轉錄因子對酵母基因的控制強度大小關係的差異性。此外使用主成份分析法(Principle Component Analysis, PCA)將60個酵母菌基因分別在四種不同的實驗作分析，了解各實驗所得主成份的基因分佈情況。

Midbody is a transient “organelle-like” structure and consists of a compact, dense matrix of proteins, which are indispensable for cytokinesis. Inappropriate regulation of midbody formation will significantly affect the terminal cytokinesis events and result in a multi-nucleate phenotype, which is a characteristic of tumorigenesis. In this study, we use human midbody genes accessed through a homology modeling strategy from time-series microarry data of 6178 cell cycle genes for S. cerevisiae and three literatures for 60 yeast genes. First, select different kinds of genes to analyze the control strength between gene and regulator, and the profiles of transcription factor by network component analysis. We compare the results from NCA with those from Tsai to inspect whether both approaches can achieve the same results. The next, analyze the four kinds of the experiments for S. cerevisiae, discuss the result by NCA. Besides, realize the principal component for 60 yeast genes in the four experiments by principal component analysis.

中文摘要 I
英文摘要 II
目錄 III
圖目錄 VII
表目錄 VII
第一章 緒論 1
1.1 前言 1
1.2 文獻回顧 2
1.2.1 K個最近鄰居法(K-Nearest Neighbors, KNN) 4
1.2.2 主成份分析法(Principal component Analysis, PCA) 5
1.2.3 K個平均分群法(K-means clustering) 5
1.2.4 網路成分分析法(Network Component Analysis,NCA) 6
1.2.5 皮爾森積差相關係數法(Pearson product-moment correlation coefficient) 7
1.3 研究動機 8
1.4 組織章節 8
第二章 方法介紹 10
2.1 基因微陣列介紹 10
2.1.1 基因微陣列矩陣的製造 11
2.1.2 基因片上的染色質體免疫沉澱技術(Chromatin Immunoprecipitation on ChIP; Chip-on-chip) 13
2.1.3 微陣列矩陣的應用 13
2.2 K個最近鄰居法(K-Nearest Neighbors, KNN) 14
2.3 主成份分析法(Principal Component Analysis, PCA) 15
2.4 K個平均分群法(K-means clustering) 16
2.5 網路成分分析法(Network Component Analysis, NCA) 17
2.6 相關係數(Correlation coefficient) 20
第三章 中心顆粒體的轉錄因子活性之推論 22
3.1 資料的選取 22
3.1.1 人類中間體蛋白基因 22
3.1.2 微陣列矩陣數據來源 23
3.1.3 連結矩陣(A)的建立 25
3.2 資料前處理 26
3.2.1 酵母菌基因的挑選 26
3.2.2 微陣列矩陣(E)的處理 26
3.2.3 轉錄因子矩陣(P)的處理 27
3.3 網路成分分析法的計算結果 27
3.3.1 轉錄因子表現的決定 28
3.3.2 轉錄因子在細胞週期中活性分佈 28
3.3.3 轉錄因子對於各個基因的控制強度關係 29
3.3.4 結果與討論 33
3.4 挑選不同基因方式的結果 35
3.4.1 網路成分分析法計算結果 35
3.4.2 結果與討論 36
3-5 總結 41
第四章 不同微陣列數據在網路成分分析的計算 43
4.1 資料的選取 43
4.2 資料前處理 44
4.2.1 酵母菌基因的挑選 44
4.2.2 微陣列矩陣及轉錄因子矩陣的處理 45
4.3 網路成分分析法的計算 45
4.3.1 轉錄因子在細胞週期中活性分佈 46
4.3.2 轉錄因子對於各個基因的控制強度關係 46
4.3.3 結果與討論 46
4.4 相關係數比較 52
4.4.1轉錄因子與轉譯前基因的相關性 52
4.4.2 轉錄因子與調控關係基因的相關性 53
4.4.3 轉錄因子與中間體基因的相關性 53
4.4.4 結果與討論 61
4.5 總結 63
第五章 酵母菌微陣列矩陣的主成分分析 64
5.1 資料的獲得 64
5.1.1 基因的取得 64
5.1.2 數據來源 64
5.2 資料前處理 64
5.3 主成分分析法的計算 67
5.3.1 主成分個數的挑選 67
5.3.2 主成分中的基因個數決定 67
5.3.3 各個主成分的基因表現 68
5.3.4 四種實驗的K個平均分群法 68
5.3.5 結果與討論 69
5.4 總結 76
第六章 結論與建議 77
6.1 結論 77
6.2 建議 78
參考文獻 79
附錄 83

1. Tsai HK, Lu HHS, Li WH: Statistical methods for identifying yeast cell cycle transcription factors. Proceedings of the National Academy of Sciences of the United States of America 2005, 102(38):13532-13537.
2. Spellman PT, Sherlock G, Zhang MQ, Iyer VR, Anders K, Eisen MB, Brown PO, Botstein D, Futcher B: Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Molecular Biology of the Cell 1998, 9(12):3273-3297.
3. Schena M, Shalon D, Davis RW, Brown PO: Quantitative monitoring of gene-expression patterns with a complementary-DNA microarray. Science 1995, 270(5235):467-470.
4. Pokholok DK, Harbison CT, Levine S, Cole M, Hannett NM, Lee TI, Bell GW, Walker K, Rolfe PA, Herbolsheimer E et al: Genome-wide map of nucleosorne acetylation and methylation in yeast. Cell 2005, 122(4):517-527.
5. Troyanskaya O, Cantor M, Sherlock G, Brown P, Hastie T, Tibshirani R, Botstein D, Altman RB: Missing value estimation methods for DNA microarrays. Bioinformatics 2001, 17(6):520-525.
6. Ding C, He XF: Cluster structure of K-means clustering via principal component analysis. In: Advances in Knowledge Discovery and Data Mining, Proceedings. vol. 3056; 2004: 414-418.
7. Yeung KY, Ruzzo WL: Principal component analysis for clustering gene expression data. Bioinformatics 2001, 17(9):763-774.
8. Driscoll ME, Gardner TS: Identification and control of gene networks in living organisms via supervised and unsupervised learning. Journal of Process Control 2006, 16(3):303-311.
9. Galbraith SJ, Tran LM, Liao JC: Transcriptome network component analysis with limited microarray data. Bioinformatics 2006, 22(15):1886-1894.
10. Kao KC, Yang Y-L, Boscolo R, Sabatti C, Roychowdhury V, Liao JC: Transcriptome-based determination of multiple transcription regulator activities in Escherichia coli by using network component analysis. PNAS 2003, 101:641-646.
11. Yang YL, Suen J, Brynildsen MP, Galbraith SJ, Liao JC: Inferring yeast cell cycle regulators and interactions using transcription factor activities. Bmc Genomics 2005, 6.
12. Liao JC, Boscolo R, Yang YL, Tran LM, Sabatti C, Roychowdhury VP: Network component analysis: Reconstruction of regulatory signals in biological systems. Proceedings of the National Academy of Sciences of the United States of America 2003, 100(26):15522-15527.
13. Zou KH, Tuncali K, Silverman SG: Correlation and simple linear regression. Radiology 2003, 227(3):617-622.
14. Kulesh DA, Clive DR, Zarlenga DS, Greene JJ: Identification of interferon-modulated proliferation-related cDNA sequences. Proceedings of the National Academy of Sciences of the United States of America 1987, 84(23):8453-8457.
15. Lashkari DA, DeRisi JL, McCusker JH, Namath AF, Gentile C, Hwang SY, Brown PO, Davis RW: Yeast microarrays for genome wide parallel genetic and gene expression analysis. Proceedings of the National Academy of Sciences of the United States of America 1997, 94(24):13057-13062.
16. Sehgal MSB, Gondal I, Dooley L: A coollateral missing value estimation algorithm for DNA microarrays. IEEE 2005:377-380.
17. Chang WC: On using principal components before separating a mixture of 2 multivariate normal-distributions. Applied Statistics-Journal of the Royal Statistical Society Series C 1983, 32(3):267-275.
18. Skop AR, Liu HB, Yates J, Meyer BJ, Heald R: Dissection of the mammalian midbody proteome reveals conserved cytokinesis mechanisms. Science 2004, 305(5680):61-66.
19. Wu JQ, Kuhn JR, Kovar DR, Pollard TD: Spatial and temporal pathway for assembly and constriction of the contractile ring in fission yeast cytokinesis. Developmental Cell 2003, 5(5):723-734.
20. Wu JQ, Pollard TD: Counting cytokinesis proteins globally and locally in fission yeast. Science 2005, 310(5746):310-314.
21. Wu JQ, Sirotkin V, Kovar DR, Lord M, Beltzner CC, Kuhn JR, Pollard TD: Assembly of the cytokinetic contractile ring from a broad band of nodes in fission yeast. Journal of Cell Biology 2006, 174(3):391-402.
22. Lee TI, Rinaldi NJ, Robert F, Odom DT, Bar-Joseph Z, Gerber GK, Hannett NM, Harbison CT, Thompson CM, Simon I et al: Transcriptional regulatory networks in Saccharomyces cerevisiae. Science 2002, 298(5594):799-804.
23. Pic A, Lim FL, Ross SJ, Veal EA, Johnson AL, Sultan MRA, West AG, Johnston LH, Sharrocks AD, Morgan BA: The forkhead protein Fkh2 is a component of the yeast cell cycle transcription factor SFF. Embo Journal 2000, 19(14):3750-3761.
24. Simon I, Barnett J, Hannett N, Harbison CT, Rinaldi NJ, Volkert TL, Wyrick JJ, Zeitlinger J, Gifford DK, Jaakkola TS et al: Serial regulation of transcriptional regulators in the yeast cell cycle. Cell 2001, 106(6):697-708.
25. Althoeder H, Schleiffer A, Wassmann K, Nordheim A, Ammerer G: Mcm1 is required to coordinate G2-specific transcription in saccharomyces cerevisiae. Molecular and Cellular biology 1995:5917-5928.
26. Oehlen L, McKinney JD, Cross FR: Ste12 and Mcm1 regulate cell cycle-dependent transcription of FAR1. Molecular and Cellular Biology 1996, 16(6):2830-2837.
27. Horak CE, Luscombe NM, Qian JA, Bertone P, Piccirrillo S, Gerstein M, Snyder M: Complex transcriptional circuitry at the G1/S transition in Saccharomyces cerevisiae. Genes & Development 2002, 16(23):3017-3033.
28. Gimeno CJ, Fink GR: Induction of pseudohyphal growth by overexpression of PHD1, a saccharomyces-cerevisiae gene-related to transcriptional regulators of fungal developement. Molecular and Cellular Biology 1994, 14(3):2100-2112.
29. Cattell RB: Scree test for number of factors. Multivariate Behavioral Research 1966, 1(2):245-276.
30. Kaiser HF: The application of electronic-computers to factor-analysis. Educational and Psychological Measurement 1960, 20(1):141-151.
31. Henry RC, Hidy GM: Multivariate-analysis of particulate sulfate and other air-quaity variables by principal components .2. salt-lake-city, utah and st-louis, missouri. Atmospheric Environment 1982, 16(5):929-943.