【摘要】：阿爾茨海默病以其高發(fā)病率和無法治愈的特點(diǎn)成為老年人的第四大“健康殺手”.迄今為止,尚不明確阿爾茨海默病的發(fā)病機(jī)理.隨著基因芯片技術(shù)的發(fā)展,基因表達(dá)數(shù)據(jù)的聚類分析方法應(yīng)用到阿爾茨海默疾病的研究中.為了挖掘阿爾茨海默病的生物信息,本文提出了一種改進(jìn)的聚類算法.通過實(shí)驗(yàn)分析,得到了阿爾茨海默病基因表達(dá)數(shù)據(jù)的特征.當(dāng)數(shù)據(jù)呈現(xiàn)出線性相關(guān)的特征時(shí),對(duì)高維數(shù)據(jù)進(jìn)行降維處理并判斷聚類趨勢(shì),得到數(shù)據(jù)具有明顯的聚類趨勢(shì),然后選擇用聚類的方法挖掘基因表達(dá)數(shù)據(jù)的潛在信息.但是傳統(tǒng)的聚類方法需要事先確定出分類個(gè)數(shù),而主觀的參數(shù)選取難以將大量的數(shù)據(jù)準(zhǔn)確地進(jìn)行聚類,而且這個(gè)參數(shù)的選取直接影響了實(shí)驗(yàn)數(shù)據(jù)的分類結(jié)果,使得聚類效果缺乏客觀性.因此,本文提出了將曲率最大處作為分類判據(jù)的無監(jiān)督聚類方法,并且給出了分類判據(jù)δ.在基于擬合方法的基礎(chǔ)上,找出四種不同患病程度下聚類的閾值和聚類結(jié)果.最后得出本文的聚類效果優(yōu)于其他聚類方法的效果.同時(shí)實(shí)驗(yàn)結(jié)果表明,這種改進(jìn)的聚類方法較優(yōu),并且簡(jiǎn)捷、具有可行性.
[Abstract]:Alzheimer's disease, with its high incidence and incurable characteristics, has become the fourth largest health killer in the elderly. So far, the pathogenesis of Alzheimer's disease remains unclear. With the development of gene chip technology, cluster analysis of gene expression data has been applied to the study of Alzheimer's disease. In order to mine the biological information of Alzheimer's disease, an improved clustering algorithm is proposed in this paper. The characteristics of Alzheimer's disease gene expression data were obtained by experimental analysis. When the data show linear correlation characteristics, the high dimensional data is reduced and the clustering trend is judged, and the clustering trend is obtained, and then the potential information of gene expression data is mined by clustering method. But the traditional clustering method needs to determine the number of classification in advance, but the subjective parameter selection is difficult to cluster a large number of data accurately, and the selection of this parameter has a direct impact on the classification results of experimental data. The clustering effect lacks objectivity. Therefore, an unsupervised clustering method using the maximum curvature as the classification criterion is proposed, and the classification criterion 未 is given. On the basis of fitting method, the threshold and clustering results of four kinds of diseases were found out. Finally, it is concluded that the clustering effect of this paper is better than that of other clustering methods. The experimental results show that the improved clustering method is simple and feasible.
【學(xué)位授予單位】：四川師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP311.13

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