A New Method for the Discovery of Essential Proteins

doi:10.1371/journal.pone.0058763

CORC > 北京大学 > 信息科学技术学院

	A New Method for the Discovery of Essential Proteins
	Zhang, Xue ; Xu, Jin ; Xiao, Wang-xin
刊名	plos one
	2013
关键词	SACCHAROMYCES-CEREVISIAE GENOME IDENTIFYING ESSENTIAL PROTEINS INTERACTION NETWORK ESSENTIAL GENES PPI NETWORK YEAST CENTRALITY TOPOLOGY INTEGRATION PREDICTION
DOI	10.1371/journal.pone.0058763
英文摘要	Background: Experimental methods for the identification of essential proteins are always costly, time-consuming, and laborious. It is a challenging task to find protein essentiality only through experiments. With the development of high throughput technologies, a vast amount of protein-protein interactions are available, which enable the identification of essential proteins from the network level. Many computational methods for such task have been proposed based on the topological properties of protein-protein interaction (PPI) networks. However, the currently available PPI networks for each species are not complete, i.e. false negatives, and very noisy, i.e. high false positives, network topology-based centrality measures are often very sensitive to such noise. Therefore, exploring robust methods for identifying essential proteins would be of great value. Method: In this paper, a new essential protein discovery method, named CoEWC (Co-Expression Weighted by Clustering coefficient), has been proposed. CoEWC is based on the integration of the topological properties of PPI network and the co-expression of interacting proteins. The aim of CoEWC is to capture the common features of essential proteins in both date hubs and party hubs. The performance of CoEWC is validated based on the PPI network of Saccharomyces cerevisiae. Experimental results show that CoEWC significantly outperforms the classical centrality measures, and that it also outperforms PeC, a newly proposed essential protein discovery method which outperforms 15 other centrality measures on the PPI network of Saccharomyces cerevisiae. Especially, when predicting no more than 500 proteins, even more than 50% improvements are obtained by CoEWC over degree centrality (DC), a better centrality measure for identifying protein essentiality. Conclusions: We demonstrate that more robust essential protein discovery method can be developed by integrating the topological properties of PPI network and the co-expression of interacting proteins. The proposed centrality measure, CoEWC, is effective for the discovery of essential proteins.; Multidisciplinary Sciences; SCI(E); PubMed; 8; ARTICLE; 3; e58763; 8
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/291384]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Zhang, Xue,Xu, Jin,Xiao, Wang-xin. A New Method for the Discovery of Essential Proteins[J]. plos one,2013.
APA	Zhang, Xue,Xu, Jin,&Xiao, Wang-xin.(2013).A New Method for the Discovery of Essential Proteins.plos one.
MLA	Zhang, Xue,et al."A New Method for the Discovery of Essential Proteins".plos one (2013).