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RBMMMDA: predicting multiple types of disease-microRNA associations

文献类型：期刊论文

作者Chen, Xing5,6; Yan, Chenggang Clarence4; Zhang, Xiaotian3; Li, Zhaohui2,9; Deng, Lixi1,8; Zhang, Yongdong7; Dai, Qionghai4
刊名SCIENTIFIC REPORTS
出版日期2015-09-08
卷号5页码:13
ISSN号2045-2322
DOI10.1038/srep13877
英文摘要Accumulating evidences have shown that plenty of miRNAs play fundamental and important roles in various biological processes and the deregulations of miRNAs are associated with a broad range of human diseases. However, the mechanisms underlying the dysregulations of miRNAs still have not been fully understood yet. All the previous computational approaches can only predict binary associations between diseases and miRNAs. Predicting multiple types of disease-miRNA associations can further broaden our understanding about the molecular basis of diseases in the level of miRNAs. In this study, the model of Restricted Boltzmann machine for multiple types of miRNA-disease association prediction (RBMMMDA) was developed to predict four different types of miRNA-disease associations. Based on this model, we could obtain not only new miRNA-disease associations, but also corresponding association types. To our knowledge, RBMMMDA is the first model which could computationally infer association types of miRNA-disease pairs. Leave-one-out cross validation was implemented for RBMMMDA and the AUC of 0.8606 demonstrated the reliable and effective performance of RBMMMDA. In the case studies about lung cancer, breast cancer, and global prediction for all the diseases simultaneously, 50, 42, and 45 out of top 100 predicted miRNA-disease association types were confirmed by recent biological experimental literatures, respectively.
资助项目National Natural Science of Foundation of China[11301517] ; National Natural Science of Foundation of China[61472203] ; National Natural Science of Foundation of China[61327902] ; National Center for Mathematics and Interdisciplinary Sciences, CAS ; State Key Laboratory of Intelligent Control and Decision of Complex Systems, Beijing Institute of Technology
WOS研究方向Science & Technology - Other Topics
语种英语
WOS记录号WOS:000360799600003
出版者NATURE PUBLISHING GROUP
源URL[http://119.78.100.204/handle/2XEOYT63/9385]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Chen, Xing
作者单位1.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
2.Tsinghua Univ, Sch Life Sci, Beijing 100084, Peoples R China
3.Shandong Univ, Sch Mech Elect & Informat Engn, Weihai 264209, Peoples R China
4.Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
5.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
6.Chinese Acad Sci, Natl Ctr Math & Interdisciplinary Sci, Beijing 100190, Peoples R China
7.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
8.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
9.Natl Inst Biol Sci, Beijing 102206, Peoples R China
推荐引用方式
GB/T 7714		 Chen, Xing,Yan, Chenggang Clarence,Zhang, Xiaotian,et al. RBMMMDA: predicting multiple types of disease-microRNA associations[J]. SCIENTIFIC REPORTS,2015,5:13.
APA Chen, Xing.,Yan, Chenggang Clarence.,Zhang, Xiaotian.,Li, Zhaohui.,Deng, Lixi.,...&Dai, Qionghai.(2015).RBMMMDA: predicting multiple types of disease-microRNA associations.SCIENTIFIC REPORTS,5,13.
MLA Chen, Xing,et al."RBMMMDA: predicting multiple types of disease-microRNA associations".SCIENTIFIC REPORTS 5(2015):13.

入库方式： OAI收割

来源：计算技术研究所

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