請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/80757完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 蕭朱杏(Chuhsing Kate Hsiao) | |
| dc.contributor.author | Ying-Ju Lai | en |
| dc.contributor.author | 賴映儒 | zh_TW |
| dc.date.accessioned | 2022-11-24T03:15:28Z | - |
| dc.date.available | 2021-11-03 | |
| dc.date.available | 2022-11-24T03:15:28Z | - |
| dc.date.copyright | 2021-11-03 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-10-14 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/80757 | - |
| dc.description.abstract | "基因差異網路分析(differential network analysis)可用於了解基因之間相關性的改變對於複雜疾病的影響。疾病與基因的關聯性研究，過去多專注於找尋基因表現量差異(differential gene expression)的生物標記(biomarker)，然而隨著生物路徑(biological pathway)與基因網路(genetic network)近年來被廣泛討論，複雜的生物機制、基因與基因之間的相關性，不論是相互抑制或是活化，都有可能造成疾病的發生；而利用基因差異網路分析能不再只針對單一個基因，而可以同時將基因之間的相關性納入考量，並且同時利用條件機率考慮到網路內全體基因。 大多數研究對於基因差異網路的建立，都需要先針對不同組別各自建立出基因網路，然後再藉由不同的統計方法，如假設檢定等，探討兩個組別顯著差異的網路連線。例如，先利用條件相關性質建立每個組別的基因網路，再利用兩個組別的條件相關係數之差異，來作為建立基因差異網路的方法。這樣的方法至少需要兩個步驟，可能花費較多計算時間；而且，建立兩個組別各自的基因網路將導致需要被估計的參數個數變得龐大。 本研究提出的方法希望能同時將兩個組別的基因資訊一同進行模型估計，使得所需要估計的參數個數較少、使用較少的模型假設、達到較快的運算速度。本研究的方式為，利用「條件相關」、「基因差異網路」以及「基因交互作用」三者，來建立基因差異網路，希望透過基因之間交互作用在不同組別間的不同，利用羅吉斯迴歸模型，來建立基因差異網路。同時，本研究也將闡明，不論是條件相關差異或是迴歸係數估計皆能得到相似的基因差異網路。 本研究透過模擬比較羅吉斯迴歸模型與其他建立差異網路的方法，例如：DINGO、INDEED、JDINAC、以及其他變數選擇的統計方法等，結果顯示羅吉斯迴歸模型在特異度(specificity)、準確度和F1-score均有很好的表現。同時，本研究也將此方法應用在兩筆不同的資料，分別為美國癌症基因體圖譜計畫(The Cancer Genome Atlas, TCGA)資料庫中子宮頸癌資料，以及台灣人體生物資料庫(Taiwan biobank)中三酸甘油酯資料。在這些實證資料分析中，藉由基因差異網路的建立，可以了解基因之間相互作用的改變對於疾病的影響。在本研究建立的差異網路中，STAT1與AKT3、MYC與RAF等基因交互作用對於卵巢癌有顯著影響，而在三酸甘油酯資料則發現SNX27與TUFT1、TUFT1與TFIP等基因交互作用，未來或許可以進一步探討其分子層次的功能與對於疾病的影響。" | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-24T03:15:28Z (GMT). No. of bitstreams: 1 U0001-1210202122003300.pdf: 10027078 bytes, checksum: a7bc82fabb96ca4ffe0619d40d478150 (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | 致謝 i 中文摘要 ii 英文摘要 iv 目錄 vi 表目錄 vii 圖目錄 viii 第一章 研究背景 1 第一節 傳統相關性分析 1 第二節 基因網路的研究目的 2 第三節 基因與基因之間的關聯性測量 4 第四節 現有基因差異網路研究 5 第二章 研究方法 8 第一節 Gaussian Graphical Model 8 第二節 羅吉斯迴歸模型 10 第三節 方法連結 11 第三章 統計模擬 18 第一節 模擬設定 18 第二節 模擬結果 21 第四章 資料分析 25 第一節 卵巢癌資料分析 25 第二節 三酸甘油脂資料分析 27 第五章 討論 30 第六章 參考文獻 33 | |
| dc.language.iso | zh-TW | |
| dc.subject | 精確度矩陣 | zh_TW |
| dc.subject | 基因網路 | zh_TW |
| dc.subject | 基因差異網路 | zh_TW |
| dc.subject | 條件相關 | zh_TW |
| dc.subject | 羅吉斯迴歸模型 | zh_TW |
| dc.subject | 交互作用 | zh_TW |
| dc.subject | logistic regression | en |
| dc.subject | precision matrix | en |
| dc.subject | interaction | en |
| dc.subject | genetic network | en |
| dc.subject | differential network analysis | en |
| dc.subject | partial correlation | en |
| dc.title | 利用基因交互作用建立基因差異網路 | zh_TW |
| dc.title | Utilizing Gene-gene Interaction for Construction of Differential Network | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.coadvisor | 盧子彬(Tzu-Pin Lu) | |
| dc.contributor.oralexamcommittee | 楊欣洲(Hsin-Tsai Liu),鍾仁華(Chih-Yang Tseng),王彥雯 | |
| dc.subject.keyword | 基因網路,基因差異網路,條件相關,羅吉斯迴歸模型,交互作用,精確度矩陣, | zh_TW |
| dc.subject.keyword | genetic network,differential network analysis,partial correlation,logistic regression,interaction,precision matrix, | en |
| dc.relation.page | 70 | |
| dc.identifier.doi | 10.6342/NTU202103675 | |
| dc.rights.note | 同意授權(限校園內公開) | |
| dc.date.accepted | 2021-10-14 | |
| dc.contributor.author-college | 公共衛生學院 | zh_TW |
| dc.contributor.author-dept | 流行病學與預防醫學研究所 | zh_TW |
| 顯示於系所單位： | 流行病學與預防醫學研究所 | |
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| U0001-1210202122003300.pdf 授權僅限NTU校內IP使用（校園外請利用VPN校外連線服務） | 9.79 MB | Adobe PDF |
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