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工程科学与技术:2014,46(5):116-120
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基于不确定网络的关键蛋白质识别
(长沙大学信息与计算科学系)
IdentificationofEssentialProteinsBasedonUncertainNetworks
(Dept.ofInfo.&ComputingSci.,ChangshaUniv.)
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投稿时间:2014-01-17    修订日期:2014-06-03
中文摘要: 考虑蛋白质相互作用网络的不可靠,构建不确定相互作用网络,提出一种名为EPU的关键蛋白质识别算法。算法采用期望稠密度作为评判一个子图能否预测为关键模块的准则,预测的模块将用于关键蛋白质识别;通过蛋白质在关键模块中出现的概率频率对蛋白质评分,分值越高,成为关键蛋白质的可能性越大。实验结果显示,EPU算法性能优于其他的关键蛋白质识别算法,是一种有别于现有方法的新型关键蛋白质识别算法。结果表明,不确定性数据管理理论有助于提高算法对蛋白质相互作用网络中噪声的鲁棒性。
Abstract:Taking into account the reliability of protein-protein interaction (PPI) network, an uncertain network was constructed and a novel method named essential proteins identification based on uncertain networks (EPU) was developed to identify essential proteins from the uncertain network. The concept of expect density was used to decide whether a subgraph can be represented as an essential module for essential proteins identification. Proteins were ranked through their probabilistic frequency appearing in these predicted modules. Then the ranking scores of these proteins were used to judge whether a protein is essential. Experimental results showed that the EPU algorithm outperforms other essential proteins prediction algorithms and is a special method which is different from others. The results indicated that the theory of uncertain data management is useful for the improvement of robustness in protein-protein interaction networks.
文章编号:201400071     中图分类号:    文献标志码:
基金项目:国家自然科学基金资助项目(60473117);湖南省自然科学基金项目(13JJ4106;14JJ3138);湖南省教育厅科学研究项目(14C0096);长沙市科技项目(K1205049-11;K1205048-11)
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胡赛,熊慧军,陈治平,赵碧海.基于不确定网络的关键蛋白质识别[J].工程科学与技术,2014,46(5):116-120.
Hu Sai,Xiong Huijun,Chen Zhiping,Zhao Bihai.IdentificationofEssentialProteinsBasedonUncertainNetworks[J].Advanced Engineering Sciences,2014,46(5):116-120.