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一种基于极大团扩展的蛋白质复合物识别算法

A new algorithm for identification of protein complexes based on clique
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摘要 后基因组时代如何识别蛋白质复合物并预测其功能是蛋白组学的一项基本任务,然而传统实验方法获取的蛋白质复合物不仅数量有限而且成本代价高昂,采用新技术和方法提高蛋白质复合物的识别效率是现阶段与蛋白质相关的药物设计唯一现实可行的手段。本文基于蛋白质相互作用网络的小世界原理和蛋白质复合物内蛋白质之间的最短距离一般不超过2的事实提出了一种新的基于极大团扩展的蛋白质复合物识别算法NCIA。该算法针对蛋白质网络中的极大团利用聚类系数进行扩展以提高蛋白质复合物识别的准确率。将该方法应用于酵母蛋白质相互作用网络,相关数据表明与其他典型的蛋白质复合物识别算法相比较,该方法具有很好的识别能力。 How to identify protein complexes and its functions is a basic task in proteomics during post-genome era. However, traditional method is limited in the number of known complexes and the expense of identifying protein complexes is very high. The new technologies and methods must be devised in or-der to improve the precision of protein complexes discovery. Our paper proposed a new algorithm for i-dentification of protein complexes, named NCIA. This algorithm is proposed based on the theory of small world and the fact that the shortest distance is less than two in protein-protein interaction network. The algorithm can improve the precision of protein complexes discovery by expanding clique with cluster property. Experiment results on yeast protein interaction network show that more known protein complex-es are recalled by NCIA than by other typical algorithms.
作者 黄新
机构地区 深圳职业技术学院计算机工程学院
出处 《饲料工业》 北大核心 2012年第13期27-31,共5页 Feed Industry
关键词 蛋白质相互作用网络 蛋白质复合物 极大团 蛋白组学 protein interaction network protein complex clique proteomics
分类号 TP301.6 [自动化与计算机技术—计算机系统结构]
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参考文献23

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二级参考文献15

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饲料工业
2012年 第13期

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