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有读书笔记有附件Predicting disease-related genes by topological similarity in human protein-protein interaction network

热3 lyshaerbin 添加于 2010-4-22 20:48 | 2817 次阅读 | 2 个评论

  •  作 者

    Zhang L, Hu K, Tang Y

  •  摘 要

    Predicting genes likely to be involved in human diseases is an important task in bioinformatics field. Nowadays, the accumulation of human protein–protein interactions (PPIs) data provides us an unprecedented opportunity to gain insight into human diseases. In this paper, we adopt the topological similarity in human protein–protein interaction network to predict disease-related genes. As a computational algorithm to speed up the identification of disease-related genes, the topological similarity has substantial advantages over previous topology-based algorithms. First of all, it provides a global measurement of similarity between two vertices. Secondly, quantity which can measure new topological feature has been integrated into the notion of topological similarity. Our method is specially designed for predicting disease-related genes of single disease-gene family. The proposed method is applied to human protein–protein interaction and hepatocellular carcinoma (HCC) data. The results show a significant enrichment of disease-related genes that are characterized by higher topological similarity than other genes.

  •  详细资料

    • 文献种类: Journal Article
    • 期刊名称: Central European Journal of Physics
    • 期刊缩写: centr.eur.j.phys.
    • ISBN: 1895-1082

  • 学科领域 生物医药 » 生物学

  •  所属群组

    bioinformatics  

  •  标 签

    疾病基因预测 

  • 相关链接 DOI URL 

  •  附 件

    PDF附件Predicting disease-related genes by topological similarity in human protein-protein interaction network 

  •  lyshaerbin 的文献笔记  订阅

    [原创]

    预测人类的疾病基因是当前生物信息学领域的重要任务。当前，大量的蛋白质互作数据为我们理解疾病提供了新的机遇。本文中，利用蛋白质互作网络中的拓扑相似性预测疾病基因。基于拓扑相似性的方法比基于拓扑性质的方法有很多的优点。首先，基于相似性的方法提供了节点的全局测度。另外，衡量拓扑特征的新测度已经整合到拓扑相似性之中。文章的方法主要是为预测single disease-gene family特殊设计的。本文的测度是拓扑相似性，与以往的基于拓扑性质的方法不同。但本文并没有具体与基于拓扑性质的方法进行比较。

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