Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/90445
標題: Application of System Computation Analysis in Biology Research and Vaccine Design
系統計算分析於生物學研究與疫苗設計之應用
作者: 胡裕仁
Yu-Jen Hu
關鍵字: 系統生物學
生物序列
模糊聚類
演化樹
疫苗開發
System Biology
Biological Sequences
Fuzzy Clustering
Phylogenetic Tree
Vaccine Development
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摘要: Recently, because of the sudden increased prevalence of human and zoonotic infectious diseases, developing the effective vaccines and targeted therapies to prevent and to alleviate the harm as well as the pain caused by disease manifestation become urgent for keeping the individual health. Using computational mathematics to analyze the developmental variations of biological systems, and to apply the derived data to the related medical sciences is an accelerated and the most economical method. In this study, we used bioinformatics and the associated statistical methods to align biological sequences and to analyze the structural homologies for the hidden features, which are targets of the related medical interests. The resultant methods could therefore be applied to develop a novel analytical platform for predicting the target epitopes, designing antigens to provoke immune responses against these specific epitopes, and applying these strategies to produce effective vaccines in time to prevent spreading of the disease. First, we design a set of procedures to automatically analyze and calculate the known biological sequences and structures. Through this system, we have designed a faster and more accurate method to obtain the required data. Using these methods, we could solve the artifactual sequences gained in experimental handlings, which could then lead to uncertainty of measurement accuracy in molecular weights. These methods can also be used to fine-tune the gene analysis instruments and to improve machine variation-caused different results. Moreover, using the same strategy, we r developed a method to utilize evolutionary tree theory to predict the possible mutation sites of influenza viruses, which might affect validity of the available vaccines. In fact, through these stratagems, we are able to estimate the possible next genetic variations in the influenza virus (H1N1) that would affect the potency of the vaccines. The actual proof of immunization effect is carrying out in an ongoing experiment. As expected, the results will be able to confirm our mathematical theory. In conclusion, we have developed specific mathematical calculation methods to fast-track analyze viral sequence variations, and to accelerate the development of effective vaccines against the devastating wide spread of potential virus infections.
近年來,由於傳染病及人畜、人禽共通疾病大量的衍生,如何開發有效疫苗與急效藥物以預防或減輕疾病對個人健康,實為當務之急。而利用數學計算以進行分析系統生物發育變化,並運用到相關之學科是最簡約的方法。 本研究論文即是以結合生物資訊及統計方法,快速分析大量的生物序列數據資料,探討類似生物間同型序列的排列結構。並藉此尋找其隱藏的生物功能,作為發展相關的生物學研究和醫藥應用,成為預測抗原特異目標胜肽、設計能產生有效抗體之抗原蛋白以及疫苗製造的新分析平臺。 首先,我們針對已知生物序列結構的生物序列設計一套能自動對序的演算方法。透過檢測工具進行分析比較,進而快速、準確地得到計算結果。此演算方法可解決生物實驗操作中經常發生的序列亂碼與分子量變異等測量問題,並可藉此改進基因分析上所發生的差異。 進一步,我們結合生物分子系統發育理論,建構綜合使用演化樹的計算方法,透過全序列比對及統計方法的估計,縮短在流行性感冒病毒疫苗研發的時程。實際上,透過這些理論,我們能預測流行性感冒病毒 H1N1 下一年可能的基因變異點,以及這種變異是否會影響疫苗之效價,真正的免疫實驗已著手進行,期待其結果能證實現在數學推算理論的確實性。 本研究論文之結果顯示,以數學計算方式,我們能具體發展出快速找出病毒序列以供製造具有專一性反應的有效疫苗區段之方法。
URI: http://hdl.handle.net/11455/90445
文章公開時間: 10000-01-01
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