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研究生： 黃楹楹
Ying-Ying Huang
論文名稱： 鑑別導致不同功能性基因表現差異之調控因子組合
Genome-wide Co-occurrence Detection of PutativeRegulatory Sites Based on Co-regulated GeneClusters in Yeast Genomes
指導教授： 洪炯宗
Jorng-Tzong Horng
口試委員:
學位類別： 碩士
Master
系所名稱： 資訊電機學院 - 資訊工程學系
Department of Computer Science & Information Engineering
畢業學年度： 91
語文別： 英文
論文頁數： 41
中文關鍵詞： 基因表現 、調控因子
外文關鍵詞： regulatory sites, transcription factor binding sites, pattern discovery, mining
相關次數： 點閱：14  下載：0 
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    • 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 Introduction 1 1.1 Motivations 1 1.2 Goals 2 1.3 Background 3 Chapter 2 Related Works 5 2.1 Pattern discovery tools 5 2.2 TRANSFAC database 8 2.3 GenBank 10 2.4 RSDB [3] 11 2.5 Functional related gene groups 11 2.6 Co-regulated gene groups 12 Chapter 3 Materials and Methods 14 3.2 Preprocessing phase 15 3.3 Prediction phase 16 3.3.1 Over-represented repeats statistics analysis 17 3.3.2 Known site homologs and DNA binding motifs discovery 19 3.4 Annotation phase 23 3.4.1 Site co-occurrence Analysis 24 3.4.2 Significance filtering 25 3.4.3 Distance filtering 29 Chapter 5 Results 30 5.1 Positional biased of motif groups 30 5.2 Group specific site combinations 31 Chapter 6 Summery 34 References 36 Appendix 39 A. Database schema of web 39 B. Comparison with other approaches 40 C. Enrichment of gene expression clusters for ORFs within MIPS functional categories 41 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 Flow 15 Figure 4. Map showing the locations of experimentally verified binding sites of Mat

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