發(fā)布時間：2018-06-01 02:11

  本文選題：網絡結構 + 二部圖　； 參考：《安徽大學學報(自然科學版)》2017年05期

【摘要】：相關疾病基因的發(fā)現(xiàn)和預測是人類基因組研究的重要目標.近些年,一些研究者通過基于網絡結構的方法來解決這個難題.然而,大多數(shù)方法在推理過程中僅使用了局部的網絡信息,并且僅限于推理單一基因的關聯(lián).并且這些方法很少考慮到疾病-基因關聯(lián)網絡的網絡拓撲性.筆者提出一種改進的基于二部圖網絡結構推理(improved network-based inference)的計算方法.該方法基于已知的疾病-基因網絡拓撲相似性來發(fā)現(xiàn)更多潛在致病基因.文中使用的是OMIM數(shù)據(jù)庫中的203種疾病的數(shù)據(jù),通過留一交叉驗證法驗證實驗,并獲得了88.9%的AUC值.與文中提到的另外兩種方法相比,該文方法能夠有效地預測潛在致病基因.
[Abstract]:The discovery and prediction of related disease genes is an important goal in the study of human genome. In recent years, some researchers have solved this problem through a network based approach. However, most of the methods use only local network information in the reasoning process, and are limited to the association of single genes. Considering the network topology of the disease gene association network, the author proposes an improved method based on the two part graph network structure reasoning (improved network-based inference). This method is based on the known disease gene network topology similarity to discover more potential pathogenic factors. The 203 species in the OMIM database are used in this paper. The data of the disease were verified by a cross validation method, and 88.9% of the AUC value was obtained. Compared with the other two methods mentioned in the article, the proposed method can effectively predict the potential pathogenic genes.
【作者單位】： 安徽大學計算智能與信號處理教育部重點實驗室;
【基金】：國家自然科學基金資助項目(61172127)
【分類號】：R319;TP301.6

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1 方明宏;基于熱擴散模型的致病基因預測方法研究[D];華中師范大學;2015年

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本文編號：1962457