臺灣博碩士論文加值系統

癌症位居國人的十大死因第一位，對於癌症治療的研究倍受重視，在臨床上，缺乏於正常細胞及腫瘤間可供辨識的專一性差異，是目前發展專一性抗癌療法的主要障礙，欲治癒腫瘤首要必須使所有腫瘤的幹細胞失去其產生子代細胞的能力。因此透過對於細胞週期的過程及其控制機轉的瞭解，進而瞭解整個癌症在惡性變性過程中的所有細節，才能對癌症做有效的治療。本篇論文便是為了使病患在接受醫療的過程中，提供一個兼具有計算功能和表現價值的醫療輔助工具，而提出了一個以“藉由遞迴類神經網路建構基因調控網路的定性模型（Qualitative Modeling of Genetic Regulatory Networks via Recurrent Artificial Neural Network）”，使得基因醫療工作者能夠模擬病患接受治療後基因的變化情形，以決定是否以該療程對該病患進行治療。
在模型中，我們假設基因調控網路已經經由實驗確定的情況下，利用遞迴類神經網路所建構出來的表示方法及計算方法，並且可以用來模擬及表示基因之間的功能相依性。這個定性模型不僅可用圖示的方式來表示基因與基因之間的相互關係，更可以將其基因彼此間的定性相互作用模擬出來。模型除了結合基因調控（Gene Regulation）、布林網路（Kauffmann, 1993）、及類神經網路外，更結合了連續的離散時間這個觀念，使得在呈現及模擬上，更加地接近真實情況，進而幫助基因工作者來瞭解和推論藥物和有毒化學物質對於基因的影響。

According to the statistical abstract from Department of Health, Taiwan, R.O.C., 2001, cancer is still in the fist place in the cause of the death. Because of this reason, the therapy of cancer is widely emphasized on. Clinically, we can not tell the specific difference between the normal cell and cancer cell. This is one of the barriers to develop the therapy of cancer. Owing to these, a proposed qualitative model in order to help gene-related-disease workers to understand and reason the effect of toxic chemicals and medicines that are capable of activating or inactivating certain genes in the treatment of gene-related diseases. In this paper, we propose to model gene regulation networks qualitatively via recurrent artificial neural network.
In this model, we assume the gene regulation network is definitive. Such a computational and representational model can reason about the interactions among related genes effectively and intuitively. It can help trace snapshots of gene regulatory dynamics at any two consecutive time steps concurrently along the discrete time line and it can help to produce what-if scenario when certain genes are activated or inactivated purposely as needed. Hence, it can serve as an auxiliary tool for gene-related-disease workers.

第1章 緒論…………………………………………………………1
1.1 背景介紹………………………………………………………3
1.2 動機與目的……………………………………………………5
第2章 基因調控………………………………………………………9
2.1 基因……………………………………………………………10
2.1.1 去氧核糖核酸………………………………………11
2.1.2 核糖核酸……………………………………………13
2.1.3 蛋白質………………………………………………16
2.1.4 蛋白質的合成………………………………………17
2.2 基因調控………………………………………………………19
第3章 類神經網路……………………………………………………26
3.1 類神經單元……………………………………………………27
3.2 Perceptron……………………………………………………30
3.3 神經組…………………………………………………………32
3.3.1 包含辨識神經組………………………………………32
3.3.2不包含辨識神經組……………………………………35
3.4 合取神經組……………………………………………………37
3.5 析取神經組……………………………………………………41
第4章 藉由遞迴類神經網路表示的基因調控網路…………………45
4.1 符號表示法……………………………………………………46
4.2 基因調控網路…………………………………………………47
4.3 藉由遞迴類神經網路建構基因調控網路……………………51
4.4 癌症與基因調控………………………………………………59
4.4.1 致癌基因和抑癌基因…………………………………59
4.4.2 致癌基因的活化………………………………………60
4.4.3 癌症的分期……………………………………………61
4.5 基因調控網路例子的探索……………………………………65
第5章 結論……………………………………………………………72
參考文獻………………………………………………………………74

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