【摘要】：近年來(lái),識(shí)別疾病的相關(guān)基因成為生命科學(xué)領(lǐng)域富有挑戰(zhàn)性的工作之一。傳統(tǒng)的預(yù)測(cè)疾病基因的方法有連鎖分析(Linkage Analysis)和關(guān)聯(lián)研究(Association Study)。但是連鎖分析方法只能定位染色體上的一段區(qū)域,這段區(qū)域包含幾十個(gè)到幾百個(gè)基因。同時(shí)關(guān)聯(lián)研究也需要明確候選基因。各國(guó)研究人員陸續(xù)的提出對(duì)這段區(qū)域的候選基因進(jìn)行進(jìn)一步篩選的方法。 人類基因組計(jì)劃(Human Genome Project, HGP)的完成和高通量生物技術(shù)的產(chǎn)生,我們獲取了大規(guī)模的人類蛋白質(zhì)交互作用數(shù)據(jù)(Protein-Protein Interaction, PPI)。有研究表明,在PPI網(wǎng)絡(luò)上,具有較高拓?fù)渲丿B的蛋白質(zhì)共屬于一個(gè)生物功能模塊或生物通路的可能性就越大�；诖�,本文中,我們提出了基于PPI網(wǎng)絡(luò)的對(duì)疾病候選基因進(jìn)行預(yù)測(cè)的方法MTOMATOM。此方法結(jié)合多點(diǎn)拓?fù)渲丿B法(Multi-node Topology Overlap Measure, MTOM)和兩點(diǎn)拓?fù)渲丿B法(Averaged Topology Overlap Measure, ATOM)。 MTOMATOM方法是通過(guò)衡量網(wǎng)絡(luò)節(jié)點(diǎn)間拓?fù)渲丿B性大小來(lái)反映網(wǎng)絡(luò)節(jié)點(diǎn)間的相似性,是一個(gè)更能反映生物意義的網(wǎng)絡(luò)距離度量法。我們把該方法在包含783個(gè)基因的110類疾病-基因家族中進(jìn)行50-fold留一法交叉驗(yàn)證,發(fā)現(xiàn)enrichment達(dá)到27-fold, roc曲線下面積為92.3%,取得了與同類方法相比較好的效果。 我們把MTOMATOM方法應(yīng)用于阿爾茨海默氏病(Alzheimer's Disease,AD)相關(guān)基因的發(fā)現(xiàn)研究。首先,在kohler等人構(gòu)建的PPI網(wǎng)絡(luò)上進(jìn)行預(yù)測(cè)分析,取得了跟kohler等人提出來(lái)的全局度量法隨機(jī)游走相同的效果。其次,基于劉等人提出來(lái)的腦特異網(wǎng)絡(luò)進(jìn)行AD基因的預(yù)測(cè),前46個(gè)分值最高的基因中,有40個(gè)與AD相關(guān)聯(lián)的基因,比劉等人的預(yù)測(cè)結(jié)果稍好。MTOMATOM方法復(fù)雜度低,運(yùn)算速度快,并且對(duì)網(wǎng)絡(luò)的不完整性和連接的假陽(yáng)性有較強(qiáng)的魯棒性。
[Abstract]:In recent years, the identification of disease-related genes has become one of the challenging tasks in life sciences. The traditional methods for predicting disease genes are linkage analysis (Linkage Analysis) and association study (Association Study). But linkage analysis can only locate a region of a chromosome that contains dozens to hundreds of genes. At the same time, association studies also need to identify candidate genes. Researchers from all over the world have proposed methods for further screening candidate genes in this region. With the completion of the Human Genome Project (Human Genome Project, HGP) and the production of high-throughput biotechnology, we have obtained large-scale human protein interaction data (Protein-Protein Interaction, PPI). Studies have shown that on PPI networks, proteins with high topological overlaps are more likely to belong to one biological functional module or biological pathway. Therefore, in this paper, we propose a method of disease candidate gene prediction based on PPI network, MTOMATOM. This method combines multi-point topology overlap method (Multi-node Topology Overlap Measure, MTOM) and two-point topological overlap method (Averaged Topology Overlap Measure, ATOM). MTOMATOM method) to reflect the similarity of network nodes by measuring the degree of topological overlap between nodes. It is a network distance measure that can reflect biological meaning more. The method was cross-validated by 50-fold method in 110 disease-gene families containing 783 genes. It was found that the enrichment reached 27-fold and the area under the roc curve was 92.3.The results were better than that of the similar methods. We applied the MTOMATOM method to the discovery of genes associated with Alzheimer's disease (Alzheimer's Disease,AD). First, the prediction analysis is carried out on the PPI network constructed by kohler et al., and the results are the same as the global metric proposed by kohler et al. Secondly, based on the brain-specific network proposed by Liu et al., 40 of the first 46 genes with the highest score are associated with AD, which is slightly better than that of Liu et al. the MTOMATOM method is less complex and faster. And it has strong robustness to the network imperfection and false positive connection.
【學(xué)位授予單位】：東北大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2009
【分類號(hào)】：R346

【共引文獻(xiàn)】

相關(guān)期刊論文 前2條

1 ;Biomarkers of Alzheimer’s disease in body fluids[J];Science China(Life Sciences);2010年04期

2 鄭妍鵬;何金生;洪濤;;阿爾茨海默病體液生物學(xué)標(biāo)記物研究進(jìn)展[J];中國(guó)科學(xué)(C輯:生命科學(xué));2009年09期

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本文編號(hào)：2268556