應用人類基因表現資料於基因表現關聯性之研究

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：53

、訪客IP：3.129.211.116

姓名

曾國炎(Kuo-Yen Tseng) 查詢紙本館藏

畢業系所

資訊工程學系

論文名稱

應用人類基因表現資料於基因表現關聯性之研究
(Correlations of Tissue Gene Expression by Analyzing Digital Expression Profiles of Human Tissues)

相關論文

★ 利用相減式雜交法鑑定小葉浮萍受巴拉刈與銅誘導之基因	★ 利用cDNA微陣列技術探討蕃茄根部組織受過量銅誘導之基因
★ 利用乳酸菌表達大腸桿菌之酸性磷酸	★ 阿拉伯芥根細胞核之有絲分裂原蛋白質激酶與蛋白質酪胺酸磷酸化受銅處理之變化
★ 小葉浮萍之色胺酸合成酵素beta鏈基因選殖與色胺酸及其衍生物受銅影響之化學分析

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限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。

摘要(中)

本研究試圖去分析現有大量來自不同人類組織的基因表現資料，去尋找那些具有規則性表現或是會同時表現於某幾種組織裡面的基因，這些基因可能具有某些生物上或是藥理學上的關聯性。在本文中，我們提出兩種不同的方式去分析那些表現在不同人類組織中的大量基因之間的關聯性，這些會特別地或是規則地表現在某些特定組織裡的關係透露出這些基因可能具有某些調控上的意義或者是屬於同一個反應路徑和訊號傳導流程的其中一環。

摘要(英)

The study attempts to analyze a large number of human genome transcription products from diverse tissues and to discover genes that are co-expressed in some different tissues. Those genes may be of potential biological or pharmaceutical relevance. We proposed two approaches to discover the correlations of gene expression by analyzing multiple expression profiles of different human tissues. The correlations of gene expression reveal that genes are specifically or regularly expressed in particular tissues simultaneously. Besides, the correlations of gene expression can be used to identify the relationships of genes which are potential to be co-regulated, involving in the same biochemical pathway or signal transduction process.

關鍵字(中)

★ 統計分析
★ 基因表現關聯性
★ 資料探勘

關鍵字(英)

★ gene expression
★ Chi-square
★ association rule
★ UniGene
★ SAGE
★ data mining

論文目次

Chapter 1 Introduction 1
Chapter 2 Related Work 7
2.1 The Property of Expressed Sequence Tags (ESTs) 7
2.2 The Property of UniGene 7
2.3 The Property of Serial Analysis of Gene Expression (SAGE) 8
2.4 The Property of Cancer Genome Anatomy Project (CGAP) 9
2.5 The Property of HomoloGene 9
2.6 Association Rules 10
2.7 Chi-square Test Statistics 11
Chapter 3 Materials and Methods 12
3.1 Materials 13
3.1.1 Human Gene Expression Profiles from UniGene 13
3.1.2 Human Gene Expression Profiles from SAGE 19
3.1.3 Mouse Gene Expression Profiles from UniGene 21
3.2 Methods 21
3.2.1 Mining Association Rules and Pruning by Chi-square 22
3.2.2 Mining Correlations using Chi-square Test 23
Chapter 4 Experiments and Results 25
4.1 Environments of Implementation 25
4.2 Experimental Results 25
4.2.1 Results after Applying Association Rules 25
4.2.2 Results after Applying Chi-square Test 28
4.3 Results Published on Web 28
Chapter 5 Conclusions 28
References 28
Appendix 28

參考文獻

[1] Agrawal, R., Imielinski, T. and Swami, A. (1993) Mining association rules between sets of items in large databases, ACM SIGMOD, 207-216.
[2] Agrawal, R. and Srikant, R. (1994) Fast Algorithms for Mining Association Rules, VLDB-94, 487-499.
[3] Ali, K., Manganaris, S. and Srikant, R. (1997) Partial classification using association rules, KDD-97, 115-118.
[4] Audic, S. and Claverie, J. M. (1997) The significance of digital gene expression profiles, Genome Res., 7:986-995.
[5] Boguski, M. S., Lowe, T. M. and Tolstoshev, C. M. (1993) dbEST -- database for "expressed sequence tags”, Nat. Genet., 4, 332-333.
[6] Brijs, T., Vanhoof, K. and Wets, G. (2000) Reducing redundancy in characteristic rule discovery by using IP-Techniques, In Intelligent Data Analysis Journal, 4 (3).
[7] Caron, H., et al. (2001) The Human Transcriptome Map: Clustering of Highly Expressed Genes in Chromosomal Domains, Science, 291, 1289-1292.
[8] Eickhoff, H., et al. (2000) Tissue gene expression analysis using arrayed normalized cDNA libraries, Genome Res., 10:1230-1240.
[9] Ewing, R.M. and Claverie, J-M. (2000) EST databases as multi-condition gene expression datasets, Pac. Symp. Biocomput., 430-442
[10] Greller, L. D. and Tobin, F. L. (1999) Detecting selective expression of genes and proteins. Genome Res., 9:282-296.
[11] Liu, B., Hsu, W. and Ma, Y. (1999) Pruning and summarizing the discovered associations,” KDD-99.
[12] Riggins, G. J. and Strausberg, R. L. (2001) Genome and genetic resources from the Cancer Genome Anatomy Project, Human Molecular Genetics, 10, 663-667.
[13] Scheurle, D., DeYoung, M. P., Binninger, D. M., Page, H., Jahanzeb, M. and Narayanan, R. (2000) Cancer gene discovery using digital differential display, Cancer Res., 60, 4037-4043.
[14] Schuler, G. D. et al. (1996) A gene map of the human genome, Science, 274, 540-546.
[15] Schuler, G. D. (1997) Pieces of the puzzle: expressed sequence tags and the catalog of human genes, J. Mol. Med., 75, 694-698.
[16] Srikant, R., Vu, Q., and Agrawal, R. (1997) Mining Association rules with item constraints, KDD-97, 67-73.
[17] Stekel, D. J., Git, Y. and Falciani, F. (2000) The comparison of gene expression from multiple cDNA libraries, Genome Res., 10:2055-2061.
[18] Toivonen, H., Klemettinen, M., Ronkainen, P, Hätönen, K, and Mannila, H. (1995) Pruning and grouping discovered association rules, Mlnet Workshop on Statistics, Machine Learning, and Discovery in Database, 47-52.
[19] Vasmatzis, G., Essand, M., Brinkmann, U., Lee, B. and Pastan, I. (1998) Discovery of three genes specifically expressed in human prostate by expressed sequence tag database analysis, Proc. Natl. Acad. Sci., 95, 300-304.
[20] Velculescu, V. E., et al. (1999) Analysis of human transcriptomes, Nat. Genet., 23, 387-388.
[21] Velculescu, V. E., et al. (1995) Serial analysis of gene expression, Science, 270, 484-487.
[22] Zhuo, D., et al. (2001) Assembly, annotation, and integration of UniGene clusters into the human genome draft, Genome Res., 11, 904-918.

指導教授

董啟功(Chi-Gong Tong)

審核日期

2002-6-27

推文