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博碩士論文 etd-0320112-103212 詳細資訊
Title page for etd-0320112-103212
論文名稱
Title
以布林邏輯式為知識基礎輔助基因調控模型之重建
A Boolean knowledge-based approach to assist reconstruction of gene regulatory model
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
76
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2012-01-12
繳交日期
Date of Submission
2012-03-20
關鍵字
Keywords
S-system、基因調控網路、布林網路、逆向工程、系統生物學
System Biology, Reverse Engineering, Gene Regulatory networks, S-system, Boolean networks
統計
Statistics
本論文已被瀏覽 5868 次,被下載 370
The thesis/dissertation has been browsed 5868 times, has been downloaded 370 times.
中文摘要
在系統生物學的領域中,了解基因調控的機制是一個相當重要的課題。隨著生物資訊科技的發展,我們透過DNA的微陣列取得大量基因作用的實驗數據。為了瞭解基因調控的關係,許多模擬基因調控網路的方法被提出。在這些模擬的調控方法中以數學模式非線性微分方程的S-system最為廣泛所使用。而透過S-system可以模擬出基因調控網路的動態行為以及基因表達波形,但是對於基因調控網路的結構以及方向性卻無法有效的解釋。因此我們提出利用布林網路的結構知識協助S-system模擬基因調控網路。
在本研究中,我們透過S-system的調控參數推導出基因之間的正負調控關係,並以布林網路的結構做為知識基礎。在S-system模擬調控網路的過程中依照8:2、7:3、5:5、3:7、2:8等結構懲罰權重進行實驗。根據實驗的結果,可以驗證我們對於S-system的調控參數的假設,並更進一步的了解基因之間的調控關係。
Abstract
Understanding the mechanisms of gene regulation in the field of systems biology is a very important issue. With the development of bio-information technology, we can capture large quantities of gene’s expression data from DNA microarray data. In order to discover the relationship of gene regulation, the simulation of gene regulatory networks have been proposed. Among these simulations methods, the S-system model is the most widely used in non-linear differential equations. It can simulate the dynamic behavior of gene regulatory networks and gene expression, but can’t explain the structure and orientation of gene regulatory networks. Therefore, we propose a Boolean knowledge-based approach to assist the S-system modeling of gene regulatory networks.
In this study, we derive the positive and negative regulatory relationships between genes from the regulation of S-system parameters, and use the structure of Boolean networks as our knowledge base. According to the results of the experiment, we can verify our assumptions for the regulation of the S-system parameters, and also has a better understanding of the regulatory relationship between genes.
目次 Table of Contents
1. 緒論 1
1.1 研究背景 1
1.2 研究動機與目的 3
1.3 問題描述 4
1.4 論文架構 4
2. 文獻探討 5
2.1 模擬基因調控網路 5
2.1.1 布林網路(Boolean Network) 5
2.1.2 微分方程式(Differential Equations) 10
2.2 方程式最佳化與評估方式 11
2.2.1 粒子群優化演算法(Particle Swarm Optimization, PSO) 11
2.2.2 參數值評估方式 14
3. 研究方法與架構 15
3.1 研究方法 15
3.1.1 布林網路結構知識推導 15
3.1.2 S-system參數推導 17
3.1.3 實驗設計 19
3.2 實驗流程與架構 21
4. 實驗結果與討論 23
4.1 實驗資料 23
4.2 人工基因 24
4.2.1 5 Node Dataset 1 24
4.2.2 5 Node Dataset 2 27
4.2.3 5 Node Dataset 3 30
4.2.4 10 Node Dataset 33
4.3 布林結構 36
4.3.1 8 Node Dataset 36
4.3.2 10 Node DATASET 39
4.3.3 R10 Node DATASET 42
4.4 實驗結果與討論 45
4.4.1 人工結構實驗結果 45
4.4.2 布林結構實驗結果 51
4.4.3 實驗討論 55
4.4.4 人工結構 55
4.4.5 布林結構 60
5. 結論與未來研究 61
6. 參考文獻 62
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