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RKNNMDA: Ranking-based KNN for MiRNA-Disease Association prediction
Chen, Xing1; Wu, Qiao-Feng2; Yan, Gui-Ying3
2017
Source PublicationRNA BIOLOGY
ISSN1547-6286
Volume14Issue:7Pages:952-962
AbstractCumulative 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.
KeywordDisease disease semantic similarity KNN algorithm miRNAs miRNA-disease association SVM Ranking model
DOI10.1080/15476286.2017.1312226
Language英语
Funding ProjectNational Natural Science Foundation of China[11631014] ; National Natural Science Foundation of China[11371355]
WOS Research AreaBiochemistry & Molecular Biology
WOS SubjectBiochemistry & Molecular Biology
WOS IDWOS:000407258600015
PublisherTAYLOR & FRANCIS INC
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/26252
Collection应用数学研究所
Corresponding AuthorChen, Xing
Affiliation1.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
Recommended Citation
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.
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