本論文探討系統理論在生物資訊之應用，首先使用李亞普諾夫函數中的穩定理論來降低接合位置數以便進一步增進分子對接的效能，並且使用NURBS曲線中的插入頂點與權重調整來加速分子系統達到最小能量狀態。其次以各種不同的藥物受體模型來做電腦模擬計算，利用最小能量原理判斷出接近全域能量最小的區域之對接狀態的穩定度，並對其各種分子活性進行評估，研究各種分子對接中的各項活性，從中瞭解分子力場各元素的貢獻度，也成功地驗證出本論文所提出的方法。
再者提出以李雅普諾夫穩定性理論探討結核病流行現狀和動力學模型的問題，結合社會網絡與倉室模型等建模方法，發展一套適合用來模擬傳染疾病的傳播動態與探討相關的公共衛生政策的成效的流行病電腦模擬模型。利用MATLAB/Simulink數值分析模擬軟體其對結核病流行，建立各種反應結核病動力學特性的數學模型，尋找對其預防和控制的最優策略，為防治決策提供理論基礎和數量依據。面對結核病流行的現狀，我們將通過生物數學模型來探討結核病的發展動態趨勢。藉由SIMR的解來模擬結核病疫情的發展，再從中尋覓控制疫情的良策；經分析模型中各參數對疫情的演化影響，發現病患隔離參數在疫情控制上扮演著最重要的角色，提出SIMR數學模型與一些數值實驗結果並加以驗證，可提供一些建議，作為結核病疫情防治決策參考。

This dissertation aims at exploring the application of system theory in in the bioinformatics, The first, Lyapunov’s stability theorem to accelerate the molecular docking system and aim at the short response route. Next, we used various drug-ligand interaction models to computed docking simulation and employed energy minimum theorem to judge the approach global energy minimum area and docking stability. We computed various molecular activities at each binding site, and observed every bond and non-bond’s contribution in force field.
Moreover, the study Lyapunov principle to deal with dynamic models for TB (Tuberculosis). Lyapunov principle is commonly used to examine and determine the stability of a dynamic system. In order to simulate the transmissions of vector-borne diseases and discuss the related health policies effects on vector-borne diseases, we combine the social network and compartmental model to develop an epidemic simulation model. The research will analyze the complex dynamic mathematic model of tuberculosis epidemic and determine its stability property by using the popular Matlab/Simulink software and relative software packages. Facing the current TB epidemic situation, the development of TB and its developing trend through constructing a dynamic bio-mathematic system model of TB is investigated. After simulating the development of epidemic situation with the solution of the SMIR epidemic model, we will come up with a good scheme to control epidemic situation to analyze the parameter values of model that influence epidemic situation evolved. We will try to find the quarantining parameters which are the most important factors to control epidemic situation. The SMIR epidemic model and the results via numerical analysis may give effective prevention with reference to control epidemic situation of TB.

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