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PRMDA: personalized recommendation-based MiRNA-disease association prediction
You, Zhu-Hong1; Wang, Luo-Pin2; Chen, Xing3; Zhang, Shanwen1; Li, Xiao-Fang1; Yan, Gui-Ying4; Li, Zheng-Wei5
2017-10-17
Source PublicationONCOTARGET
ISSN1949-2553
Volume8Issue:49Pages:85568-85583
AbstractRecently, researchers have been increasingly focusing on microRNAs ( miRNAs) with accumulating evidence indicating that miRNAs serve as a vital role in various biological processes and dysfunctions of miRNAs are closely related with human complex diseases. Predicting potential associations between miRNAs and diseases is attached considerable significance in the domains of biology, medicine, and bioinformatics. In this study, we developed a computational model of Personalized Recommendation-based MiRNA-Disease Association prediction (PRMDA) to predict potential related miRNA for all diseases by implementing personalized recommendation-based algorithm based on integrated similarity for diseases and miRNAs. PRMDA is a global method capable of prioritizing candidate miRNAs for all diseases simultaneously. Moreover, the model could be applied to diseases without any known associated miRNAs. PRMDA obtained AUC of 0.8315 based on leave-one-out cross validation, which demonstrated that PRMDA could be regarded as a reliable tool for miRNA-disease association prediction. Besides, we implemented PRMDA on the HMDD V1.0 and HMDD V2.0 databases for three kinds of case studies about five important human cancers in order to test the performance of the model from different perspectives. As a result, 92%, 94%, 88%, 96% and 88% out of the top 50 candidate miRNAs predicted by PRMDA for Colon Neoplasms, Esophageal Neoplasms, Lymphoma, Lung Neoplasms and Breast Neoplasms, respectively, were confirmed by experimental reports.
KeywordmiRNA disease miRNA-disease association personalized recommendation
DOI10.18632/oncotarget.20996
Language英语
Funding ProjectNational Natural Science Foundation of China[61772531] ; National Natural Science Foundation of China[11631014] ; National Natural Science Foundation of China[61572506] ; National Natural Science Foundation of China[11371355] ; Pioneer Hundred Talents Program of Chinese Academy of Sciences
WOS Research AreaOncology ; Cell Biology
WOS SubjectOncology ; Cell Biology
WOS IDWOS:000413077800087
PublisherIMPACT JOURNALS LLC
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/26759
Collection应用数学研究所
Affiliation1.Xijing Univ, Dept Informat Engn, Xian, Shaanxi, Peoples R China
2.Wuhan Univ, Int Software Sch, Wuhan, Hubei, Peoples R China
3.China Univ Min & Technol, Sch Informat & Control Engn, Xuzhou, Peoples R China
4.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
5.Sch Comp Sci & Technol, Hefei, Anhui, Peoples R China
Recommended Citation
GB/T 7714
You, Zhu-Hong,Wang, Luo-Pin,Chen, Xing,et al. PRMDA: personalized recommendation-based MiRNA-disease association prediction[J]. ONCOTARGET,2017,8(49):85568-85583.
APA You, Zhu-Hong.,Wang, Luo-Pin.,Chen, Xing.,Zhang, Shanwen.,Li, Xiao-Fang.,...&Li, Zheng-Wei.(2017).PRMDA: personalized recommendation-based MiRNA-disease association prediction.ONCOTARGET,8(49),85568-85583.
MLA You, Zhu-Hong,et al."PRMDA: personalized recommendation-based MiRNA-disease association prediction".ONCOTARGET 8.49(2017):85568-85583.
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