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研究生:劉泰佑
研究生(外文):Tai-Yu Liu
論文名稱:微陣列資料之互相調控基因之探勘
論文名稱(外文):Mining co-regulated gene pairs from microarray data
指導教授:陳倩瑜
指導教授(外文):Chien-Yu Chen
學位類別:碩士
校院名稱:元智大學
系所名稱:生物科技暨生物資訊研究所
學門:生命科學學門
學類:生物科技學類
論文種類:學術論文
論文出版年:2005
畢業學年度:93
語文別:中文
論文頁數:20
中文關鍵詞:互相調控基因微陣列資料
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分析基因表現的資料可以幫助我們更加瞭解基因之間互相調控的關係。然而,現有的分析方法在找尋互相調控基因的關係上,結果都還不盡理想。首先,基因表現的量測值含有許多雜訊,因而影響後續的分析結果。另一方面,現有的多種分析方法結果一致性偏低,顯示不同方法其實偵測到不同種類的調控關係。過去的實驗結果顯示,儘管將不同的方法所尋找到的配對關係整合起來,仍無法涵蓋所有目前已知的調控關係,因此開發新的分析方法輔助原有尋找調控關係的方法仍有其必要性。本論文在分析流程的前後階段分別搭配進一步的統計檢定,期望在這個問題上能獲得更好的結果。首先,我們使用過去研發的方格顯著檢測方法檢查每一個基因在一特定時間點的表現值相較於其他基因或其他時間點是否具有顯著的統計意義,此部分的實驗結果顯示此方法有助於提升原有偵測調控關係方法的品質。本論文更進一步以卡方統計檢定為基礎設計一個新的方法尋找具有調控關係的基因配對,實驗結果顯示我們提出的方法除了可以找到比過去方法更多的調控關係,且同時與過去方法具有互補的作用,顯示搭配多種方法以增進尋找調控基因配對的準確性確實有其必要性。
Analyzing gene expression data helps us to understand the regulation relationships between the genes. However, the existing analysis methods for identifying regulation relationships between genes are still not satisfied. First, the gene expression data usually contains miscellaneous noises, therefore affecting the follow-up analysis. Besides, consistency among many existing analysis methods is quite low, This demonstrates that different methods actually capture different types of regulation relationships. We observed that combining the regulation relationships found by different methods is still not able to cover all known regulation relationships. So, developing new analysis methods to complement the other original methods is desired. This thesis aims to incorporate more statistical mechanisms during the first and second stages of the analysis process, in order to provide a better solution for this problem. We first employed the test on cubical significance that we proposed previously on gene expression data to examine the gene values derived from experiments. The experimental results show that incorporating this statistical test improves the performance of two famous methods for identifying regulatory gene pairs. Furthermore, this thesis design a new method based on the chi-square test in statistics , in order to detect some other gene pairs that cannot be found by the previously published works. Our experimental results reveal that developing a robust mechanism for combining various approaches is urgently desired.
第一章 導論 1
第二章 相關工作 3
第三章 方法 5
3 – 1 資料集 5
3 – 2 方格顯著檢測 6
3 – 3 利用卡方檢定檢測基因調控關係 8
3 – 4 流程圖 10
第四章 結果 11
4 – 1 資料 11
4 – 2 事件方法與相關係數方法的實驗結果 12
4 – 3 加入方格統計檢定提升涵蓋率 13
4 – 4 利用卡方檢定為基礎尋找更多的調控關係 14
第五章 結論與未來方向 18
參考文獻 19
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