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研究生: 江益志
論文名稱: 整合基因表現量、單一核苷酸多態性標記及基因交互作用之訊息建構基因網路
Integrating gene expression, SNP markers, and gene-gene interaction towards network reconstruction
指導教授: 謝文萍
口試委員:
學位類別: 碩士
Master
系所名稱: 理學院 - 統計學研究所
Institute of Statistics
論文出版年: 2010
畢業學年度: 98
語文別: 英文
論文頁數: 37
中文關鍵詞: 基因表現量單一核苷酸多態性標記基因交互作用貝氏基因網路
外文關鍵詞: gene expression, SNP markers, gene-gene interaction, Bayesian network
相關次數: 點閱:1下載:0
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  • High-throughput technology enables the genome-wide study in almost every field of biology. However, the majority of current researches are focused on the “single gene” approach, neglecting the information about the correlation structures across genes. In this study, we take into account the correlation structure using modules as our study units. We first find the functional gene modules and then identify the corresponding SNPs by Sparse Partial Least Square method for each module. Finally, the Bayesian network is built on both the genes within the modules and the SNPs underlying the modules to re-construct the pathways associated with the well-known cancer genes in order to realize the causal relationships within the gene regulatory network.


    1. Introduction 2 1.1. Module identification 2 1.2. Module SNP mapping 2 1.3. Causal network construction 2 2. Methods 2 2.1. Module Identification 2 2.2. Module SNP Mapping 2 2.3. Network reconstruction 2 3. Results 2 3.1. Data description 2 3.2. Results of module identification 2 3.3. Results of module SNP identification 2 3.4. Results of Bayesian network 2 4. Discussion and Conclusion 2 References 2

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