本文選題：阿爾茨海默病　切入點(diǎn)：基因表達(dá)　出處：《四川師范大學(xué)》2012年碩士論文　論文類型：學(xué)位論文

【摘要】：阿爾茨海默病是癡呆病中最普通、最常見的一種�；颊弑憩F(xiàn)為記憶力逐漸衰退甚至喪失,認(rèn)知功能受阻。據(jù)2010年的統(tǒng)計(jì)數(shù)據(jù)顯示,我國的老年癡呆癥患者已己超過600萬人。阿爾茨海默病已成為威脅老年人健康的最主要的疾病之一,目前還沒有治療阿爾茨海默病的有效辦法。因此,尋找治療阿爾茨海默病的根本方法已迫在眉睫。已有研究證明,了解阿爾茨海默病的致病原理,是尋找有效治療方法的根本途徑。其關(guān)鍵在于識別阿爾茨海默病的致病基因。通過基因芯片技術(shù)得到的基因表達(dá)數(shù)據(jù)龐大,樣本眾多,要快速找到阿爾茨海默病的候選致病基因必須找到一個恰當(dāng)?shù)那腥朦c(diǎn)。如果找到與已知致病基因相關(guān)的基因,其很有可能是阿爾茨海默病的候選致病基因。目前已經(jīng)被證實(shí)的阿爾茨海默病的致病基因有載脂蛋白E(APOE),早老素基因1(presenilins1)和早老素基因2(presenilins2)。本文正是以已知的致病基因?yàn)橹行?設(shè)計(jì)算法,找出與已知致病基因相關(guān)的基因,作為為生物驗(yàn)證的候選基因。主要研究內(nèi)容如下： 首先,理解并掌握基本蟻群算法的原理、模型及實(shí)現(xiàn)步驟,了解本文的數(shù)據(jù)來源和掌握數(shù)據(jù)結(jié)構(gòu)； 其次,建立基因序列函數(shù),結(jié)合基本蟻群算法和K均值聚類算法創(chuàng)建本文獨(dú)有的算法模式,并對本文設(shè)計(jì)的算法進(jìn)行修改、完善。 最后,利用本文的算法,找到已知致病基因的伴隨基因,即阿爾茨海默病的候選致病基因,得出結(jié)論。
[Abstract]:Alzheimer's disease is the most common and most common form of dementia. It is characterized by a gradual decline in memory and loss of cognitive function. Alzheimer's disease has become one of the most important diseases threatening the health of the elderly, and there is no effective treatment for Alzheimer's disease. It is urgent to find a fundamental way to treat Alzheimer's disease. It has been proved that understanding the pathogenesis of Alzheimer's disease, Is the fundamental way to find an effective treatment. The key is to identify the genes that cause Alzheimer's disease. To quickly find candidate genes for Alzheimer's disease, you have to find the right entry point. If you find a gene associated with a known pathogenetic gene, It is very likely that it is a candidate gene for Alzheimer's disease. At present, the pathogenetic genes of Alzheimer's disease are apolipoprotein (APOEO), presenilins1 (1) and presenilins 2 (2). This paper focuses on known pathogenetic genes. The algorithm is designed to find out the genes related to known pathogenic genes as candidate genes for biological verification. The main contents of this study are as follows:. First of all, understand and master the basic ant colony algorithm principle, model and implementation steps, understand the data source and grasp the data structure; Secondly, the gene sequence function is established, combined with basic ant colony algorithm and K-means clustering algorithm, the unique algorithm pattern is created, and the algorithm designed in this paper is modified and improved. Finally, using the algorithm in this paper, we find the adjoint gene of known pathogenicity gene, that is, the candidate pathogenic gene of Alzheimer's disease, and draw a conclusion.
【學(xué)位授予單位】：四川師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2012
【分類號】：R749.16

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本文編號：1610128