博碩士論文 108826013 詳細資訊




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姓名 涂順良(Shun-Liang Tu)  查詢紙本館藏   畢業系所 系統生物與生物資訊研究所
論文名稱 藉助模塊化網路策略尋找普濟方之治療疾病 核心配方
(Investigation of Novel Core Formula for Diseases from Pu Ji Fang by Using Modularity Network Approach)
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檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   至系統瀏覽論文 (2026-10-13以後開放)
摘要(中) 中藥學的知識流傳千年,而自古以來,中醫古書就一直被拿來參考並且用於治療患者,無論是外傷或是內科雜病,近年來都有不少文獻提及中藥良好的治療效果,我們選擇權威性極高的《普濟方》當作資料分析的背景資料庫。
在先前的實驗中,已經成功透過細胞學實驗證實了利用Apriori關聯規則分析找出外傷藥核心模組的可行性。我們認為藥材-方劑網路圖搭配關聯規則分析的成效有限,網路圖中的方劑可能會影響到點的分布,於是我們將網路圖改成藥材-藥材網路圖並導入模塊化的概念重新計算金瘡、刺瘡、杖瘡門的核心模組,此套運算方式可以直接明確地分出不同的藥材族群,我們發現結果不僅與之前的實驗相符,甚至能看到更多有加減方可能性的藥物存在。於是,我們選了瘰癧門、癰疽門、痔漏門、諸蟲獸傷門這些同為外傷類的資料以及內科雜症中的諸痺門資料作比較。最後,我們發現各門之間的核心藥物組合有一定的差別性,另外也能看出藥材組合的方向,像是針對症狀不同時期的藥物以及治療相同症狀的替代藥物等,而諸痺門在《普濟方》中原本就有分類,我們在比對之後發現不同種類的痺症也有不一樣的核心模組,往後可期待這套方法更成熟時,可以更迅速且明確地找出新奇的模組。
摘要(英) The knowledge of Traditional Chinese Medicine (TCM) has been handed down for thousands of years. In recent years, there have been many documents mentioning the good therapeutic effects of Traditional Chinese Medicine, whether it is trauma or internal diseases. We use "Pu-Ji Fang" as database for data analysis. In previous experiments, cytology experiments have successfully confirmed the feasibility of using Apriori association rule analysis to find the drug-related modules. We believe that the effect of the drug-to-prescription network diagram with association rule analysis is limited, and the prescriptions in the network diagram may affect the distribution of nodes, so we changed the network diagram into a drug-to-drug network diagram and introduced the concept of modularity. Recalculate the core modules of Jin-Chuang-Phylum, Zhang-Chuang-Phylum, and Chih-Chuang-Phylum data, and we found that the results are not only in line with previous experiments, but even more possibilities for addition and subtraction can be seen. Therefore, we selected other data for comparison. We found that there are certain differences in the drug combination between each Phylum. In the future, we can expect that when this method is more precise, we can find the novel modules more quickly and clearly.
關鍵字(中) ★ 傳統中藥
★ 普濟方
★ 網路圖
★ 關聯規則
★ 模塊化
關鍵字(英) ★ Traditional Chinese Medicine
★ Pu-Ji Fang
★ association rules
★ modularity
★ network
論文目次 中文摘要 i
Abstract ii
表目錄 v
圖目錄 vii
補充表目錄 viii
補充圖目錄 x
緒論 1
1-1中醫藥學 1
1-2普濟方 2
1-3 中藥配伍 4
1-4方劑學用藥理論 4
1-5清冠一號 5
1-6生物資訊與人工智慧 6
1-7 關聯性規則(Association Rules) 6
1-8 在中醫古書中利用大數據分析找出關聯模組 7
實驗材料與方法 8
2-1 普濟方資料收集 8
2-3 Python 9
2-4 Gephi 10
2-5 模塊度(Modularity) 10
2-6 力導向布局 11
實驗結果 12
3-1 建立資料庫 12
3-2 方劑挑選 13
3-3 各門藥物分析結果 15
3-3-1金瘡、杖瘡、刺瘡門 15
3-3-2諸蟲獸傷門 17
3-3-3瘰癧門 21
3-3-4癰疽門 32
3-3-5痔漏門 49
3-3-6諸痺門 58
討論 60
參考文獻 62
補充資料 65
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19.李新為(2020)。利用生物資訊策略找出普濟方內加速傷口癒合的新配方。國立中央大學系統生物與生物資訊研究所碩士論文。(指導教授:蘇立仁)
20.醫砭,中醫症狀鑑別診斷學(2008)。檢自http://yibian.hopto.org/shu/?sno=6
(Apr.20,2021)
指導教授 蘇立仁(Li-Jen Su) 審核日期 2021-10-13
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