本文選題：乙型肝炎病毒 + 最優(yōu)風(fēng)險與預(yù)防模式��； 參考：《昆明理工大學(xué)》2013年碩士論文

【摘要】：乙型肝炎病毒(Hepatitis B virus,HBV)感染作為嚴(yán)重影響人類健康的疾病之一,是導(dǎo)致慢性肝臟疾病、肝硬化和肝癌的主要原因。HBV由于其自身復(fù)制的特殊性,具有高變異特性。據(jù)研究表明HBV基因變異是HBV持續(xù)感染的根本原因。同時在自然選擇或隨機演化的過程中,研究HBV進化演變,找出病毒起源也很重要。因此進行我國乙型肝炎病毒基因變異與系統(tǒng)進化演變的研究對于了解現(xiàn)今乙型肝炎病毒的發(fā)病機制和指導(dǎo)臨床治療提供了一定的參考依據(jù)。 為了了解HBV的基因變異情況,檢測HBV序列的SNP位點即單突變位點已廣泛應(yīng)用于大量的研究,所檢測出的SNP位點對指導(dǎo)臨床有重要意義。但是目前關(guān)于SNP位點檢測的方法多因技術(shù)難度較高,費用大等不利因素而受到制約。因此,探討一種基于計算機的SNP位點檢測方法成為一種趨勢。在本課題中,針對HBV序列的SNP位點的特點,我們提出了一種基于最優(yōu)風(fēng)險與預(yù)防模式的HBV序列的SNP位點檢測方法。所提出的方法首次應(yīng)用于HBV序列的SNP位點檢測,實驗結(jié)果表明：該方法不僅有效的檢測出HBV序列的X基因片段和前C區(qū)基因片段中已經(jīng)報道的SNP位點,而且還發(fā)現(xiàn)了一些新的位點。與硬件檢測SNP位點不同的是,所提出的計算機方法具有操作簡單和費用低的優(yōu)點,而且普通實驗室和醫(yī)療機構(gòu)均可以承受。 其次,HBV序列在進化過程中只有少量突變的位點,除此之外大都保留遺傳給了后代或者在進化過程消失。因此建立系統(tǒng)進化樹可以直觀的反映出HBV序列進化的關(guān)系,有助于了解HBV進化歷史和進化機制�；诖�,本文提出了一種新的系統(tǒng)進化樹構(gòu)建方法。該方法首先采用MEME(Multiple EM for Motif Elicitation)算法來挖掘HBV模體(Motif),然后利用新的序列度量指標(biāo)CI(Conservation Index,保守指數(shù))構(gòu)建HBV序列的系統(tǒng)進化樹,最后利用進化距離對已構(gòu)建的系統(tǒng)進化樹進行可靠性評估。實驗結(jié)果表明：新的序列度量標(biāo)準(zhǔn)CI可以有效的構(gòu)建HBV序列系統(tǒng)進化樹,分析HBV序列之間的進化關(guān)系。
[Abstract]:Hepatitis B virus (HBV) infection, as one of the serious diseases affecting human health, is the main cause of chronic liver disease, liver cirrhosis and liver cancer. Studies have shown that HBV gene mutation is the root cause of HBV persistent infection. In the process of natural selection or random evolution, it is also important to study the evolution of HBV and find out the origin of the virus. Therefore, the study on the genetic variation and phylogenetic evolution of hepatitis B virus in China provides a certain reference for understanding the pathogenesis of hepatitis B virus and guiding clinical treatment. In order to understand the variation of HBV gene, the single mutation site (SNP) of HBV sequence has been widely used in many researches. The detected SNP site is of great significance in guiding clinical practice. However, the current methods of SNP locus detection are restricted by some unfavorable factors, such as high technical difficulty and high cost. Therefore, it is a trend to explore a computer-based SNP site detection method. In this paper, according to the characteristics of SNP loci of HBV sequences, we propose a SNP locus detection method based on optimal risk and prevention mode. The proposed method is applied to the detection of SNP sites in HBV sequences for the first time. The experimental results show that the proposed method is not only effective in detecting the X gene fragments of HBV sequences and SNP sites reported in pre-C region gene fragments, but also in the detection of SNP sites in HBV sequences. Some new sites were also found. Different from hardware detection of SNP sites, the proposed computer method has the advantages of simple operation and low cost, and can be borne by both general laboratories and medical institutions. Secondly, there are only a few mutation sites in the evolution of HBV sequence. In addition, most of HBV sequences are inherited to offspring or disappeared during evolution. Therefore, the establishment of phylogenetic tree can directly reflect the evolution of HBV sequence, which is helpful to understand the history and mechanism of HBV evolution. Based on this, a new method of constructing phylogenetic tree is proposed. In this method, the MEME-Multiple EM for motif Elicitation algorithm is used to mine HBV motif motifs, and then a new sequence metric, CIGCA Conservation Index (conservative index), is used to construct the phylogenetic tree of HBV sequences. Finally, the evolutionary distance is used to evaluate the reliability of the constructed phylogenetic tree. The experimental results show that the new sequence metric CI can effectively construct the phylogenetic tree of HBV sequences and analyze the evolutionary relationship between HBV sequences.
【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：R512.62;TP311.13

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本文編號：2048739