RKNNMDA: Ranking-based KNN for MiRNA-Disease Association prediction

doi:10.1080/15476286.2017.1312226

CSpace > 应用数学研究所

	RKNNMDA: Ranking-based KNN for MiRNA-Disease Association prediction
	Chen, Xing 1; Wu, Qiao-Feng 2; Yan, Gui-Ying3
	2017
发表期刊	RNA BIOLOGY
ISSN	1547-6286
卷号	14 期号:7 页码:952-962
摘要	Cumulative verified experimental studies have demonstrated that microRNAs (miRNAs) could be closely related with the development and progression of human complex diseases. Based on the assumption that functional similar miRNAs may have a strong correlation with phenotypically similar diseases and vice versa, researchers developed various effective computational models which combine heterogeneous biologic data sets including disease similarity network, miRNA similarity network, and known disease-miRNA association network to identify potential relationships between miRNAs and diseases in biomedical research. Considering the limitations in previous computational study, we introduced a novel computational method of Ranking-based KNN for miRNA-Disease Association prediction (RKNNMDA) to predict potential related miRNAs for diseases, and our method obtained an AUC of 0.8221 based on leave-one-out cross validation. In addition, RKNNMDA was applied to 3 kinds of important human cancers for further performance evaluation. The results showed that 96%, 80% and 94% of predicted top 50 potential related miRNAs for Colon Neoplasms, Esophageal Neoplasms, and Prostate Neoplasms have been confirmed by experimental literatures, respectively. Moreover, RKNNMDA could be used to predict potential miRNAs for diseases without any known miRNAs, and it is anticipated that RKNNMDA would be of great use for novel miRNA-disease association identification.
关键词	Disease disease semantic similarity KNN algorithm miRNAs miRNA-disease association SVM Ranking model
DOI	10.1080/15476286.2017.1312226
语种	英语
资助项目	National Natural Science Foundation of China[11631014] ; National Natural Science Foundation of China[11371355]
WOS研究方向	Biochemistry & Molecular Biology
WOS类目	Biochemistry & Molecular Biology
WOS记录号	WOS:000407258600015
出版者	TAYLOR & FRANCIS INC
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/26252
专题	应用数学研究所
通讯作者	Chen, Xing
作者单位	1.China Univ Min & Technol, Sch Informat & Control Engn, 1 Daxue Rd, Xuzhou 221116, Jiangsu, Peoples R China 2.Zhejiang Univ, Coll Elect Engn, Hangzhou, Zhejiang, Peoples R China 3.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Chen, Xing,Wu, Qiao-Feng,Yan, Gui-Ying. RKNNMDA: Ranking-based KNN for MiRNA-Disease Association prediction[J]. RNA BIOLOGY,2017,14(7):952-962.
APA	Chen, Xing,Wu, Qiao-Feng,&Yan, Gui-Ying.(2017).RKNNMDA: Ranking-based KNN for MiRNA-Disease Association prediction.RNA BIOLOGY,14(7),952-962.
MLA	Chen, Xing,et al."RKNNMDA: Ranking-based KNN for MiRNA-Disease Association prediction".RNA BIOLOGY 14.7(2017):952-962.