博碩士論文 88522062 詳細資訊




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姓名 黃茁淳(Cho-Chun Huang )  查詢紙本館藏   畢業系所 資訊工程研究所
論文名稱 應用資料探勘技術於預測生物體中之基因轉錄調控因子
(Applying Data Mining to Predict Regulatory Elements)
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摘要(中) 轉錄是生物由DNA序列產生RNA的過程,轉錄因子是否黏合於促進區域及由哪些轉錄因子黏合控制著轉錄動作是否進行。本文標記轉錄因子及重複序列於基因前的促進區域,應用資料探勘(Data Mining)技術於重複序列及轉錄因子的組合,並且從關聯性規則中找出較有意義的,並且去除多餘的規則,從在規則裡的重複序列中找尋可能的轉錄因子。我們進行的實驗主要是在酵母菌的基因組上。在轉錄因子的研究上,我們得到相當有價值的資訊。
摘要(英) The process of transcription is that an RNA product produced from the DNA. Some proteins, called transcription factors, influence the transcription of genes. In this thesis, we first mark the transcription factor binding sites and repeat sequences in the promoter region of genes and then apply data mining techniques to mine the association rules from the combinations of binding sites and repeat sequences. We further prune the discovered associations to remove those insignificant associations and find a set of useful rules. We apply our approach on Yeast and mine many putative binding sites.
關鍵字(中) ★ 促進區
★  基因表現
★  調控因子
★  資料探勘
關鍵字(英) ★ Data Mining
★  Gene Expression
★  Promoter region
★  Regulatory Element
論文目次 Chapter 1Introduction1
Chapter 2Related Work6
2.1The Properties of Repeat Sequences in the Repeat Sequence Database (RSDB)6
2.2The properties Transcription Factor Binding Sites in TRANSFAC7
2.3The Properties of MIPS10
2.4Association Rules10
2.5Research of Regulatory Elements14
Chapter 3Our Approach16
3.1Materials16
3.2Statistics Analysis of Over-Represented Repetitive Oligo-mers17
3.3Classifying the Statistics by Function and Filtering the Significant Repetitive Elements19
3.4Preprocessing and Mapping20
3.5Mining Association Rules and Pruning by Chi-square21
Chapter 4Experiments and Results25
4.1Environments of Implementation25
4.2Experiments Results25
4.3Results published on Web31
Chapter 5Conclusions33
References34
Appendix A37
Appendix B39
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[2]A. Brazma, J. Vilo, E. Ukkonen and K. Valtonen, “Data Mining for Regulatory Elements in Yeast Genome”, Proc. of the Fifth International Conference Intelligent Systems for Molecular Biology, AAAI Press, 65-74(1997).
[3]Bing Liu, Wynne Hsu and Yiming Ma, “Pruning and Summarizing the Discovered Associations”, Proc. of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Diego, CA, USA, 125-134(August, 1999).
[4]H. Toivonen, M. Klemettinen, P. Ronkainen, K. Hatonen, and H. Mannila, “Pruning and grouping discovered association rules”, MLnet Workshop on Statistics, Machine Learning, and Discovery in Database, Heraklion, Crete, Greece, 47-52(April, 1995).
[5]J.D., Hughes, P.W. Estep, S. Tavazoie, and G.M. Church, “Computational Identification of cis-regulatory elements associated with groups of functionally related genes in Saccharomyces cerevisiae”, Journal of Molecular Biology, 296(2000), 1205-1214.
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[8]J.T. Horng and W.F. Cho, “Predicting Regulatory Elements in Repetitive Sequences Using Transcription Factor Binding Sites”, Electronic Journal of Biotechnology, vol 3, 3, Issue of Dec. 15, (2000).
[9]J. van Helden, Alma. F. Rios and J. Collado-Vides, “Discovering regulatory elements in non-coding sequence by analysis of spaced dyads”, Nucleic Acids Research, 28(2000), 8, 1808-1818.
[10]J. van Helden, Alma. F. Rios and J. Collado-Vides, “Extracting regulatory sites from the upstream region of yeast genes by computational analysis of oligonucleotide frequencies”, Journal of Molecular Biology, 281(1998), 827-842.
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[12]K. Ali, S. Manganaris and R. Srikant, “Partial Classification Using Association Rules”, KDD, 115-118(1997).
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[14]M. Klemettinen, H. Mannila, P. Ronkainen, H. Toivonen, and A. I. Verkamo, “Finding Interesting Rules from Large Sets of Discovered Association Rules”, CIKM, 401-407(1994).
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[16]R. Agrawal and R. Srikant, “Fast Algorithms for Mining Association Rules”, Proc. of the 20th Int’l Conference on Very Large Database, Santiago, Chile, Sept. 1994. Expanded version available as IBM Research Report RJ9839, 487-499(June, 1994).
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[18]R. Srikant, and R. Agrawal, “Mining Generalized Association Rules”, Proc. of the 21th Int’l Conference on Very Large Databases, Zurich, Switzerland, Sep, 1995. Expanded version available as IBM Research Report RJ 9963, 407-419(June, 1995).
[19]R. Srikant, Q. Vu and R. Agrawal, “Mining Association Rules with Item Constraints”, in KDD:67-73(1997).
[20]T.G. Wolfsberg, A.E. Gabrielian, M.J. Campbell, R.J. Cho, J.L. Spouge, and D. Landsman, “Candidate Regulatory Seqeunce Elements for Cell Cycle-Dependent Transcription in Saccharomyces cerevisiae”, Genome Research 9(8), 775-792 (1999).
[21]T. Heinemeyer, E. Wingender, I. Reuter, H. Hermjakob, A.E. Kel, O.V. Kel, E.V. Ignatieva, E.A. Ananko, O.A. Podkolodnaya, F.A. Kolpakov, N.L. Podkolodny and N.A. Kolchanov, “Databases on transcriptional regulation: TRANSFAC, TRRD and COMPEL”, Nucleic Acids Research, 26, 362-367(1998).
[22]T. Heinemeyer, X. Chen, H. Karas, A.E. Kel, O.V. Kel, I. Liebich, T. Meinhardt, I. Reuter, F. Schacherer and E. Wingender, “Expanding the TRANSFAC database towards an expert system of regulatory molecular mechanisms”, Nucleic Acids Research. 27, 318-322(1999).
指導教授 洪炯宗(Jorng-Tzong Horng) 審核日期 2001-7-4
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