KMS Of Academy of mathematics and systems sciences, CAS
| 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 Publication | ONCOTARGET
 |
| ISSN | 1949-2553 |
| Volume | 8Issue:49Pages:85568-85583 |
| Abstract | Recently, 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. |
| Keyword | miRNA disease miRNA-disease association personalized recommendation |
| DOI | 10.18632/oncotarget.20996 |
| Language | 英语 |
| Funding Project | National 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 Area | Oncology ; Cell Biology |
| WOS Subject | Oncology ; Cell Biology |
| WOS ID | WOS:000413077800087 |
| Publisher | IMPACT JOURNALS LLC |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/26759 |
| Collection | 应用数学研究所 |
| Corresponding Author | Chen, Xing |
| Affiliation | 1.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. |
| Files in This Item: | There are no files associated with this item. | |||||
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment