B型肝炎病毒酵素切割點分析系統與e抗體預測之研究

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B型肝炎病毒酵素切割點分析系統與e抗體預測之研究
著者: 張幃杰; Chang, Wei-Jay
孫光天; Koun-Tem Sum; 資訊教育研究所碩士班
主題: 類神經網路; B型肝炎病毒; 基因型態; genotype; neural network; HVB
描述: B型肝炎病毒基因型與抗病毒藥物治療反應有相當的關係。本研究希望定義出每一種B型肝炎病毒基因型的特性，除了可藉此建立新的方式來檢定B型肝炎病毒的基因型之外，也藉此了解不同基因型B型肝炎病毒的表現對藥物的反應度、抗藥性突變株的出現以及臨床表現的關係。為了定義出每一種B型肝炎病毒基因型的特性，已由NCBI的基因庫內搜尋約400條B型肝炎病毒基因序列，並利用Clustal X進行基因比對，再利用Mega system（Neighbor-Joining 和 Kimura 2-parameter）將基因序列分類為八大類且歸類為基因型A~H（每一組歸類都與因庫內確定基因型的序列比對完成）。將這些基因序列歸類後，本研究希望利用分析軟體找出不同基因型的病毒序列中conserved region，指出不同基因型病毒的conserved region之差異性，一併指出不同基因型的特性。藉由此分析軟體及資訊，建立新的檢定B型肝炎病毒基因型的方法。並且在取得病人的檢測數據後，以類神經網路來預測病人在未來的期間內是否可能會有轉態的情況發生。
HBV genotype may impact the response of antiviral treatment. HBV include seven genotypes (A to H) which are categorized by analysis of viral nucleotide sequences. This classification of HBV strains in terms of genome sequence has been proven to be a great tool in understanding of HBV epidemiology and evolution.In addition, different HBV genotype produces special genetic, structural, and clinically significant differences. Response to antiviral treatment and long-term prognosis may differ depending on which genotype has infected the patient. In order to characterize the HBV genome among the different genotype and establish a perfect method to identify HBV genotype in infected patients, the HBV genome sequence about 400 sequences from NCBI database were downloaded and aligned by Clustal X. These sequences were sorted into seven groups of HBV genotypes and also showed to phylogenic tree by the Neighbor-Joining and Kimura 2-parameter of Mega system. After sorting these sequences into seven genotypes, the analysis software will help us to know which consensus regions are specific in the genome of different HBV genotypes and what the expression rate is. On the other hand, the highly mutation region will be also detected in the analysis system. Therefore, the character among different HBV genotypes will be identified and a new perfect method which identified HBV genotypes will be set up. After acquiring paients’diagnostic insults, we will adopt neural network to predict whether e seroconversion could happen or not in the fature.
碩士
建立日期: 2005
格式: 121 bytes
text/html
語言: 中文
識別號: http://nutnr.lib.nutn.edu.tw/handle/987654321/5452
資源來源: NUTN IR

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B型肝炎病毒酵素切割點分析系統與e抗體預測之研究

張幃杰; Chang, Wei-Jay 孫光天; Koun-Tem Sum; 資訊教育研究所碩士班 2005

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