RKNNMDA: Ranking-based KNN for MiRNA-Disease Association prediction
文献类型：期刊论文
| 作者 | Chen, Xing1; Wu, Qiao-Feng2; Yan, Gui-Ying3
|
| 刊名 | RNA BIOLOGY
 |
| 出版日期 | 2017 |
| 卷号 | 14期号:7页码:952-962 |
| 关键词 | Disease disease semantic similarity KNN algorithm miRNAs miRNA-disease association SVM Ranking model |
| ISSN号 | 1547-6286 |
| DOI | 10.1080/15476286.2017.1312226 |
| 英文摘要 | 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. |
| 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 |
| 语种 | 英语 |
| WOS记录号 | WOS:000407258600015 |
| 出版者 | TAYLOR & FRANCIS INC |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/26251]  |
| 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. |
入库方式： OAI收割
来源：数学与系统科学研究院
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