臺灣博碩士論文加值系統

本文標記轉錄因子, 重複序列和工具預測出的黏合序列定位於基因前的促進區域。應用資料探 (Data Ming) 技術於重複序列與轉錄因子的組合以及工具預測出的黏合序列與轉錄因子的組合。再從關聯規則中去除多餘的規則．利用統計方法找出較有意義的，在規則裡的重複序列和工具預測出的黏合序列中找尋可能的轉錄因子。由於不同的轉錄因子組合的黏合會造成基因的轉錄有所不同，因此我們找出不同功能之相關基因較具鑑別性的組合。我們進行的實驗主要是酵母菌及原蟲的基因組上。轉錄因子的研究上，我們得到相當有價值的資訊，並將結果公開在http://dbms68.csie.ncu.edu.tw/REDB/ 網站上。

The data mining approach, mining association rules, is applied to mine the associations from the combinations of candidate regulatory sites and known regulatory sites. We apply a set of statistical algorithms to characterization of the site combinations in a co-regulated gene group and statistically analyzed it to other co-regulated gene groups to find the site combinations which prefer to occur in a specific gene groups with significant occurrences. The regulatory sites of the gene group-specific site combinations are putative transcription factor binding sites. The methodology introduced here facilitates to analyze combinatorial interactions of multiple transcription factors and is applied to two organisms, Saccharomyces cerevisize and Caenorhabditis elegans, and the promoter regions of ORFs of them. The results are now available at http://dbms68.csie.ncu.edu.tw/REDB/

Contents
Chapter 1 Introduction1
1.1 Motivations1
1.2 Goals2
1.3 Background3
Chapter 2 Related Works5
2.1 Pattern discovery tools5
2.2 TRANSFAC database8
2.3 GenBank10
2.4 RSDB [3]11
2.5 Functional related gene groups11
2.6 Co-regulated gene groups12
Chapter 3 Materials and Methods14
3.2 Preprocessing phase15
3.3 Prediction phase16
3.3.1 Over-represented repeats statistics analysis17
3.3.2 Known site homologs and DNA binding motifs discovery19
3.4 Annotation phase23
3.4.1 Site co-occurrence Analysis24
3.4.2 Significance filtering25
3.4.3 Distance filtering29
Chapter 5 Results30
5.1Positional biased of motif groups30
5.2 Group specific site combinations31
Chapter 6 Summery34
References36
Appendix39
A.Database schema of web39
B.Comparison with other approaches40
C. Enrichment of gene expression clusters for ORFs within MIPS functional categories41

List of Figures
Figure 1. The transcriptional regulation of a gene.4
Figure 2. Top periodic clusters, their motifs and overall distribution in all clusters.13
Figure 3. System Flow15
Figure 4. Map showing the locations of experimentally verified binding sites of Mat□2, Gcn4, Pho4, and Gal4 in upstream regions.22
Figure 5. Example of a mapping between the motif groups.25
Figure 6. A contingency table to show the genes containing sites “aaatat” and “ttgaa”.26

List of Tables
Table 1. The transcription factors and their binding sites in TRANSFAC[2] (Release 5.4).10
Table 2. The partial statistics of repetitive sequences on upstream of gene set of Amino-acid transport functional category.19
Table 3. The number of candidate regulatory sites discovered in the Yeast upstream regions.20
Table 4. The amount of known regulatory sites and over-represented repetitive sequences (OR-repeats) located in the upstream regions of each functional related gene group.30
Table 5. The co-occurrences of known and putative regulatory sites in the site combination (CATCC=>ttt.tt) in the co-regulated gene expression cluster of “cluster 6”..31
Table 6. Group-motifs of gene expression cluster 7, 14, 30 show high similarity measure and high position bias.31
Table 7. Partial significant associations mined in each of the gene expression cluster clusters.32
Table 8. The site combination mined in each functional related gene group. 433
Table 9. Combination significance & Correlation Coefficient of Combination.33
Table 10. Comparison with other approaches40
Table 11. Periodicity index is a quantitative measure of cell-cycle periodicity.41

References
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