A Computational Method Based on the Integration of Heterogeneous Networks for Predicting Disease-Gene Associations

doi:10.1371/journal.pone.0024171

	A Computational Method Based on the Integration of Heterogeneous Networks for Predicting Disease-Gene Associations
	Guo, Xingli 1,2; Gao, Lin 1; Wei, Chunshui 1; Yang, Xiaofei 2; Zhao, Yi 3; Dong, Anguo 4
	2011-09-02
发表期刊	PLOS ONE
ISSN	1932-6203
卷号	6 期号:9 页码:10
摘要	The identification of disease-causing genes is a fundamental challenge in human health and of great importance in improving medical care, and provides a better understanding of gene functions. Recent computational approaches based on the interactions among human proteins and disease similarities have shown their power in tackling the issue. In this paper, a novel systematic and global method that integrates two heterogeneous networks for prioritizing candidate disease-causing genes is provided, based on the observation that genes causing the same or similar diseases tend to lie close to one another in a network of protein-protein interactions. In this method, the association score function between a query disease and a candidate gene is defined as the weighted sum of all the association scores between similar diseases and neighbouring genes. Moreover, the topological correlation of these two heterogeneous networks can be incorporated into the definition of the score function, and finally an iterative algorithm is designed for this issue. This method was tested with 10-fold cross-validation on all 1,126 diseases that have at least a known causal gene, and it ranked the correct gene as one of the top ten in 622 of all the 1,428 cases, significantly outperforming a state-of-the-art method called PRINCE. The results brought about by this method were applied to study three multi-factorial disorders: breast cancer, Alzheimer disease and diabetes mellitus type 2, and some suggestions of novel causal genes and candidate disease-causing subnetworks were provided for further investigation.
DOI	10.1371/journal.pone.0024171
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[60933009] ; Specialized Research Fund for the Doctoral Program of Higher Education[200807010013]
WOS研究方向	Science & Technology - Other Topics
WOS类目	Multidisciplinary Sciences
WOS记录号	WOS:000294686100018
出版者	PUBLIC LIBRARY SCIENCE
引用统计	被引频次：21[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/13087
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Guo, Xingli
作者单位	1.Xidian Univ, Sch Comp Sci & Technol, Xian, Shaanxi Prov, Peoples R China 2.Xidian Univ, Sch Software Engn, Xian, Shaanxi Prov, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China 4.Changan Univ, Sch Sci, Xian, Shaanxi Prov, Peoples R China
推荐引用方式 GB/T 7714	Guo, Xingli,Gao, Lin,Wei, Chunshui,et al. A Computational Method Based on the Integration of Heterogeneous Networks for Predicting Disease-Gene Associations[J]. PLOS ONE,2011,6(9):10.
APA	Guo, Xingli,Gao, Lin,Wei, Chunshui,Yang, Xiaofei,Zhao, Yi,&Dong, Anguo.(2011).A Computational Method Based on the Integration of Heterogeneous Networks for Predicting Disease-Gene Associations.PLOS ONE,6(9),10.
MLA	Guo, Xingli,et al."A Computational Method Based on the Integration of Heterogeneous Networks for Predicting Disease-Gene Associations".PLOS ONE 6.9(2011):10.