臺灣博碩士論文加值系統

根據統計在已開發國家和開發中國家，癌症發生率機率高，可以說是人類健康的敵人，一般人在一生中罹患癌症的機率是四分之一，隨著生態環境的破壞，生活習慣和飲食習慣的改變，癌症罹患率每年不斷的上升，因此對癌症發生原因的研究是相當重要的課題，但是醫學研究人員在取得醫學文獻時卻遇到資訊過量的問題，再加上要從大量的資訊當中以人工方式取出重要資訊，不但浪費時間也容易造成錯誤。本研究的目標是發展一平台來整合、收集、分析以及預測癌症相關基因(cancer-related gene)的資訊。本論文我們利用NCBI的PubMed搜尋引擎來搜尋癌症相關基因的醫學文獻(medical literature)與序列(sequence)，根據使用者輸入的癌症名稱和LOH (loss of heterozygosity)或CGH (comparative genomic hybridization)做組合進行文獻的收集、分類、以及探勘，在癌症相關基因預測的部份，利用選擇性剪接(alternative splicing)的特性區分各正常組織與不正常組織的各種選擇性剪接表現型態，並且找出選擇性剪接表現形式以及特殊的序列樣本(pattern)。本論文提出的方法能夠探勘出重要資訊以及能了解各組織的特性，能加快醫學研究人員的研究並可節省許多時間，另外也可以將此方法應用到其他疾病上。

According to statistics, the rate of having cancer is relatively high for people in developing and developed countries. So cancer can be called as the enemy of human health. With the destruction of ecological environment and with the change of life style and diet, the rate of having cancer during the life of a general individual is one and a quarter and grows continuously by year. Thus, it is important to study the cause of cancer. However, while biomedical researchers search and retrieve biomedical literature, there is a problem of information overloading. Therefore, to survey thousands and hundreds of biomedical literatures by manual browsing is time wasting and difficult to make sure whether required information can be found. Besides, artificial inattention may lead to incorrect analysis information. The purpose of this study is to develop an integrated system for collecting，mining cancer-related gene and prediction cancer-related gene. This system uses PubMed search engine of NCBI to search and retrieve biomedical literature and sequence of cancer-related gene. Users can combine cancer name and LOH (loss of heterozygosity), or cancer name and CGH (comparative genomic hybridization) to search, retrieve, collect, classify, and extract the biomedical literatures.This system use character of alternative splicing to search for alternative splicing forms and sequences patterns. This system can extract important information to accelerate the study and save plenty of time for biomedical researchers. Besides, this system can also be used on other diseases

摘要 i
Abstract ii
目錄 iii
圖目錄 vi
表目錄 viii
表目錄 viii
第一章 緒論 1
1.1研究背景 1
1.2研究動機 2
1.3研究目的 3
1.4研究方法 3
1.5研究架構 4
第二章 相關研究 5
2.1生物相關研究 5
2.1.1 中心法則 5
2.1.2 RNA剪接(splicing) 6
2.1.3選擇性剪接(Alternative splicing) 7
2.1.4 SR蛋白質(Serine/arginine-rich protein) 9
2.1.5基因體雜交比較法(Comparative Genomic Hybridization，CGH)與異型接合缺失(Loss of Heterozygosity，LOH) 10
2.2醫學文獻探勘 11
2.3選擇性剪接 13
2.4資料庫 15
2.4.1 MeSH 15
2.4.2 PubMed 16
2.4.3 Entrez Gene 17
2.4.4 RefSeq 18
2.4.5 Ensembl 19
2.4.6 GeneCards 20
第三章 研究架構 21
3.1 研究流程 21
3.2 系統架構 22
3.4資料來源收集 24
3.4.1癌症相關資訊收集 24
3.4.2基因相關資訊收集 25
3.4.3基因序列收集 27
3.4.4相關醫學文獻收集 30
3.5醫學文獻的探勘 32
3.6分類選擇性剪接之序列 35
3.7選擇性剪接之表現形式 36
3.8選擇性剪接序列樣本 38
第四章 實作與結果 41
4.1癌症相關基因探勘 41
4.2選擇性剪接之表現形式 45
4.3特殊序列樣本 54
4.4結合SR蛋白之序列樣本 62
第五章 結論與未來研究方向 66
5.1結論 66
5.2未來研究方向 67
參考文獻 68
附錄A 癌症資訊 71
附錄B 基因組織分類 75
附錄C 二維關聯分析 79
附錄D 選擇性剪接表現形式 85
附錄E 特殊序列樣本 91
附錄F 結合SR蛋白之序列樣本 97
附錄G 論文發表 107
誌 謝 132
簡 歷 133

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