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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 莊曜宇(Eric Y. Chuang) | |
dc.contributor.author | Hung-I Harry Chen | en |
dc.contributor.author | 陳鴻毅 | zh_TW |
dc.date.accessioned | 2021-06-13T01:32:33Z | - |
dc.date.available | 2008-07-24 | |
dc.date.copyright | 2007-07-24 | |
dc.date.issued | 2007 | |
dc.date.submitted | 2007-07-16 | |
dc.identifier.citation | [1] Lengauer,C., Kinzler,K.W. and Vogelstein,B.:Genetic instabilities in human cancers. Nature, 396, 1998, 643–649.
[2] Weil R. Lai, Mark D. Johnson, Raju Kucherlapati and Peter J. Park: Comparative analysis of algorithms for identifying amplifications and deletions in array CGH data. Bioinformatics Vol. 21 no. 19 2005, 3763–3770. [3] John Quackenbush: Microarray data normalization and transformation. Nature Genetics, Vol. 32, 2002, 496 – 501. [4] Bolstad B, Irizarray R, Astrand M. and Speed T: A Comparison of Normalization Methods for High Density Oligonucleotide Array Data Based on Bias and Variance. Bioinformatics, 19, 2003, 185–193. [5] Alvin W. Moore, Jr., and James W. Jorgenson: Median Filtering for Removal of Low-Frequency Background Drift. Anal. Chem. 65, 1993, 188-191. [6] Ignacy Misztal and Miguel Perez-Enciso: Sparse Matrix Inversion for Restricted Maximum Likelihood Estimation of Variance Components by Expectation-Maximization. Journal of Dairy Science, Vol.76, 1993, 1479-1483. [7] A Kallioniemi, OP Kallioniemi, D Sudar, D Rutovitz, JW Gray, F Waldman, and D Pinkel: Comparative Genomic Hybridization for Molecular Cytogenetic Analysis of Solid Tumors. Science, vol. 258, 1992, 818–821. [8] Tarnowski BI, Spinale FG, Nicholson JH: DAPI as a useful stain for nuclear quantitation. Biotech. Histochem. 66, 1991, 297-302. [9] N. B. Ostroverkhova, S. A. Nazarenko, and A. D. Cheremnykh: Comparative Genomic Hybridization as a New Method for Detection of Genomic Imbalance. Russian Journal of Genetics, Vol. 38, No. 2, 2002, pp. 95–104. Translated from Genetika, Vol. 38, No. 2, 2002, 149–160. [10] Pinkel D, Segraves R, Sudar D, Clark S, Poole I, Kowbel D, Collins C, Kuo WL, Chen C, Zhai Y, Dairkee SH, Ljung BM, Gray JW, Albertson DG: High resolution analysis of DNA copy number variation using comparative genomic hybridization to microarrays. Nat. Genet., 20, 1998, 207–211. [11] Ludwig Wilkens MD, Joelle Tchinda, Dagmar Burkhardt, Martina Nolte DVM, Martin Werner MD and Axel Georgii MD: Analysis of hematologic diseases using conventional karyotyping, fluorescence in situ hybridization (FISH), and comparative genomic hybridization (CGH). Human Pathology, Volume 29, Issue 8, 1998, 833-839. [12] Pollack,J.R., Perou,C.M., Alizadeh,A.A., Eisen,M.B., Pergamenschikov,A., Williams,C.F., Jeffrey,S.S., Botstein,D. and Brown,P.O: Genome-wide analysis of DNA copy-number changes using cDNA microarrays. Nat. Genet., 23, 1999, 41–46. [13] Brennan C, Zhang Y, Leo C, Feng B, Cauwels C, Aguirre AJ, Kim M, Protopopov A, Chin L: High-resolution global profiling of genomic alterations with long oligonucleotide microarray. Cancer Res., 64, 2004, 4744–4748. [14] Robert Lucito, John Healy, Joan Alexander, Andrew Reiner, Diane Esposito, Maoyen Chi, Linda Rodgers, Amy Brady, Jonathan Sebat, Jennifer Troge, Joseph A. West, Seth Rostan, Ken C.Q. Nguyen, Scott Powers, Kenneth Q. Ye, Adam Olshen, Ennapadam Venkatraman, Larry Norton and Michael Wigler: Representational Oligonucleotide Microarray Analysis: A High-Resolution Method to Detect Genome Copy Number Variation. Genome Res., 13, 2003, 2291–2305. [15] Pollack,J.R, Sørlie,T., Perou,C.M., Rees,C.A., Jeffrey,S.S., Lonning,P.E., Tibshirani,R., Botstein,D., Borresen-Dale,A.L. and Brown,P.O: Microarray analysis reveals a major direct role of DNA copy number alteration in the transcriptional program of human breast tumors. Proc. Natl Acad. Sci., USA, 99, 2002, 12963–12968. [16] Daniel Pinkel and Donna G. Albertson: COMPARATIVE GENOMIC HYBRIDIZATION. Annu. Rev. Genomics Hum. Genet. 2005. 6:331–54. [17] Ishkanian AS, M.C., Watson SK, DeLeeuw RJ, Chi B, Coe BP, A.D. Snijders A, Pinkel D, Marra MA, Ling V, MacAulay C, and L. WL: A tiling resolution DNA microarray with complete coverage of the human genome. Nature Genet., vol.36, 2004, 299-303. [18] Daniel Pinkel and Donna G Albertson: Array Comparative Genomic Hybridization and Its Applications in Cancer. Nature Genetics (Supplement), Vol.37, June 2005, pp. S11- S17. [19] Schena M, Shalon D, Davis RW, Brown PO: Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 1995, 270:467-470. [20] Mehrnoush Khojasteh, Wan L Lam, Rabab K Ward and Calum MacAulay: A stepwise framework for the normalization of array CGH data. BMC Bioinformatics 2005, 6:274 [21] Sven Bilke, Qing-Rong Chen, Craig C. Whiteford and Javed Khan: Detection of low level genomic alterations by comparative genomic hybridization based on cDNA micro-arrays. Bioinformatics Vol. 21 no. 7 2005, 1138–1145. [22] Yoganand Balagurunathan, Edward R. Dougherty, Yidong Chen, Michael L. Bittner, and J. M. Trent: Simulation of cDNA Microarrays via a Parameterized Random Signal Model. Journal of Biomedical Optics. 7(3), 2002, 507-523. [23] Jörg Dahmen, Daniel Keysers, Hermann Ney and Mark Oliver Güld: Statistical Image Object Recognition using Mixture Densities. Journal of Mathematical Imaging and Vision, Vol. 14, No. 3, 2001, 285-296. [24] Yuanyuan Ding and Dawn Wilkins: The Effect of Normalization on Microarray Data Analysis. DNA and Cell Biology, Vol. 23, No. 10, 2004, 635 -642. [25] Dale J. Poirier: Piecewise regression using cubic spline. Journal of American Statistical Association, Vol. 68, No.343, 1973, 515-524. [26] Christopher Workman, Lars Juhl Jensen, Hanne Jarmer, Randy Berka, Laurent Gautier, Henrik Bjørn Nielsen, Hans-Henrik Saxild, Claus Nielsen, Søren Brunak and Steen Knudsen: A new non-linear normalization method for reducing variability in DNA microarray experiments. Genome Biology. 3(9), 2002. [27] Alaxander Zien, Thomas Aigner, Ralf Zimmer and Thomas Lengauer: Centralization: a new method for the normalization of gene expression data. Bioinformatics, Vol.17, 2001, 323-331. [28] Vojtech Franc and Vaclav Hlavac: Statistical Pattern Recognition Toolbox for Matlab User’s guide. 2004. [29] S. Kim, H. Li, E.R. Dougherty, N. Cao, Y. Chen, M.L. Bittner, and E.B. Suh: Can Markov Chain Mimic Biological Regulation? Journal of Biological Systems, 10(4), 2002, 337-358. [30] Sohrab P. Shah, Xiang Xuan, Ron J. DeLeeuw, Mehrnoush Khojasteh, Wan L. Lam, Raymond Ng and Kevin P. Murphy: Integrating copy number polymorphisms into array CGH analysis using a robust HMM. Bioinformatics, Vol. 22 no. 14 2006, pages e431–e439. [31] Sanju Attoor, Edward R. Dougherty, Yidong Chen, Michael L. Bittner, Jeffrey M. Trent: Which is better for cDNA-microarray-based classification: ratios or direct intensities. Bioinformatics, 20(16), 2004, 2513-2520. [32] Chao-Chi Ho, Pei-Hsin Huang, Hsin-Yi Huang, Yen-Ho Chen, Pan-Chyr Yang and Su-Ming Hsu: Up-Regulated Caveolin-1 Accentuates the Metastasis Capability of Lung Adenocarcinoma by Inducing Filopodia Formation. American Journal of Pathology, 161, 2002, 1647-1656. [33] http://www.invitrogen.com/content.cfm?pageid=11001 [34] Product note of Agilent Human, Mouse and Rat Genome CGH Microarrays, 244A and 105A. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/30045 | - |
dc.description.abstract | 基因體的變異是腫瘤生成發展的主因之一。已經有許多的研究證明DNA序列拷貝數的異常對癌症致病是有重大的相關性。比較基因體雜合微陣列(array CGH)是依據基因表現的微陣列晶片的技術所研發,其可以以高解析度找出染色體上序列拷貝數的變異。然而,由於array CGH先天上的特性,許多針對基因表現的資料所使用的分析工具,如資料正規化演算法,通常無法得到令人滿意的結果。在此我們闡述一個新的array CGH正規化演算法,其可以利用在array CGH實驗中,染色體上相鄰位置探針的相依性來提供精準的array CGH資料的正規化。
為了驗證此正規化演算法的表現,我們也利用隱馬爾可夫模型(HMM)來發展一套模擬系統,其可以模擬出有隨機DNA序列拷貝數變化的array CGH實驗的資料組。另外,我們也將我們的演算法去對CL1-0, CL1-1和CL1-5這三種細胞株的array CGH實驗資料作正規化來比較之間的結果。 CL1-0, CL1-1和CL1-5是依據不同的侵入性作分類,之間關係極為接近的肺癌細胞株。經由正規化後,不只使資料的品質顯著的改善,也強化了實驗結果的可靠度。藉由這個新發展的演算法,正規化後的資料呈現顯著的DNA序列拷貝數變化。最後,以此演算法為基礎,我們未來也將建立一個對使用者友善的線上系統來提供方便的array CGH資料的分析。 | zh_TW |
dc.description.abstract | Genomic instability is one of fundamental factors in tumorigenesis and tumor progression. Many studies have shown that copy-number abnormalities at the DNA level are important in the pathogenesis of cancer. Array Comparative Genomic Hybridization (array CGH), developed based on expression microarray technology, can reveal the chromosomal aberrations in segmental copies at a high-resolution. However, due to the nature of array CGH, many standard expression data processing tools, such as data normalization, often failed to yield satisfactory results. We demonstrate a novel array CGH normalization algorithm, which provides an accurate array CGH data normalization by utilizing the dependency of neighboring probe measurements in array CGH experiments.
To facilitate the study, we have developed a Hidden Markov Model (HMM) to simulate a series of array CGH experiments with random DNA copy number alterations that can be used to validate the performance of our normalization. In addition, we applied our algorithm to normalize real data from an array CGH study of CL1-0, CL1-1 and CL1-5 cell lines. CL1-0, CL1-1 and CL1-5 are closely related lung cancer cell lines which are classified according to their differential invasiveness. The normalization made significant improvement over data quality and enhanced the reliability of experimental results. By using this newly developed algorithm, the normalized data showed distinct patterns of DNA copy number alternations among those lung cancer cell lines. Finally, based on this new development; we are establishing a user-friendly web-based system to provide convenient online array CGH data analysis. | en |
dc.description.provenance | Made available in DSpace on 2021-06-13T01:32:33Z (GMT). No. of bitstreams: 1 ntu-96-R94921059-1.pdf: 1747918 bytes, checksum: a0ea84b87e3d2fa8a8218cdf4478d1eb (MD5) Previous issue date: 2007 | en |
dc.description.tableofcontents | 口試委員會審定書 ……………………………………………………… I
謝誌 ………………………………………………………………………. II 中文摘要 ………………………………………………………………….. III Abstract …………………………………………………………………….. IV Chapter 1 Introduction ……………………………………………………… 1 1.1 Background and Motivation of the Study …………………………. 1 1.2 The purpose and framework of the study ……………………….... 2 Chapter 2 Introductions to Array Comparative Genomic Hybridization …... 5 2.1 Comparative Genomic Hybridization Analysis …………………… 5 2.2 Array Comparative Genomic Hybridization ……………………... 7 Chapter 3 Materials and Methods ………………………………................. 11 3.1 Ridge-tracing Normalization Algorithm ………………................. 12 3.1.1 Quantile Normalization…………………………………… 13 3.1.2 2D Kernel Smoothing Algorithm…………………………. 15 3.1.3 Regression Methods ...……………………………………. 16 3.2 Probe Ratio Distribution and Mode Detection …….....………….. 21 3.3 Array CGH Simulation by Hidden Markov Model …….………… 24 3.4 Validation By Using Real aCGH Data ………………………….. 28 3.4.1 CL1-0, CL1-1, and CL1-5 Cell Lines …………………….. 29 3.4.2 HEEBO Microarray ……………………………………….. 29 3.4.3 Agilent Microarray ………………………………………… 29 Chapter 4 Results ...………………………………………………………..... 31 4.1 Performance of Ridge-Tracing and Normalization Algorithm ……. 32 4.2 Probe Ratio Mode Determination and aCGH Data Centralization … 33 4.3 Comparison of Four Regression Methods …….……………………. 38 4.4 Applications of Normalization Algorithm to aCGH Hybridization … 41 4.4.1 Results of HEEBO Microarray………………………………. 42 4.4.2 Results of Agilent Microarray……………………………….. 46 Chapter 5 Discussion …………………..…………………………………….. 50 Chapter 6 Conclusion …..……………………………………………………. 54 References .………..………………………………………………………… 56 圖 目 錄 Figure 1-1 The architecture of our development ………………………… 4 Figure 2-1 Scheme of the basic steps of CGH analysis …………………. 6 Figure 2-2 Scheme of array CGH experiment …………………………… 9 Figure 2-3 Examples of array CGH profiles on Chromosome 1 …………. 9 Figure 2-4 Factors which influence the success of array CGH …………… 10 Figure 3-1 Array CGH data and visualization …………………………… 11 Figure 3-2 An example and the flow chart of quantile normalization ....... 14 Figure 3-3 The identical distribution normalized by quantile normalization …………………………………………………. 15 Figure 3-4 Logistic function (with | |
dc.language.iso | en | |
dc.title | 發展一嶄新之比較基因體雜合微陣列正規化演算法 | zh_TW |
dc.title | Development of a Normalization Algorithm for Array Comparative Genomic Hybridization | en |
dc.type | Thesis | |
dc.date.schoolyear | 95-2 | |
dc.description.degree | 碩士 | |
dc.contributor.coadvisor | 陳一東(Yidong Chen) | |
dc.contributor.oralexamcommittee | 陳中明,歐陽彥正,蔡孟勳 | |
dc.subject.keyword | 基因體雜合微陣列,去氧核醣核酸拷貝數,正規化,向心化,隱馬爾可夫模型, | zh_TW |
dc.subject.keyword | Array CGH,DNA copy numbers,Normalization,Centralization,Hidden Markov Model, | en |
dc.relation.page | 69 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2007-07-17 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 電機工程學研究所 | zh_TW |
顯示於系所單位: | 電機工程學系 |
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