Title: Functional similarities between microRNAs inferred from biomedical texts

Authors: Lun Li; Libin Zhang; Zhaowan Yang; Yiran Huang; Yanhong Zhou; Huailan Liu

Addresses: Hubei Bioinformatics and Molecular Imaging Key Laboratory, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; Biomedical Engineering Department, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China ' Hubei Bioinformatics and Molecular Imaging Key Laboratory, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; Biomedical Engineering Department, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China ' Hubei Bioinformatics and Molecular Imaging Key Laboratory, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; Biomedical Engineering Department, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China ' Hubei Bioinformatics and Molecular Imaging Key Laboratory, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; Biomedical Engineering Department, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China ' Hubei Bioinformatics and Molecular Imaging Key Laboratory, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; Biomedical Engineering Department, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China ' School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China

Abstract: MicroRNAs (miRNAs) are involved in multiple biological processes, such as tumorigenesis and differentiation. The functions of most miRNAs still remain elusive. Measuring functional similarity between miRNAs is an important step to predict the functions of novel miRNAs and further identify disease-related miRNAs. In this study, we applied a biomedical text-mining method to assess miRNA functional similarities. According to validations, miRNA functional similarities inferred from biomedical texts are reliable and have the potential to distinguish disease miRNA pairs from random ones. Therefore, we further applied this set of similarity scores to uncover disease-related miRNAs, and achieved a high AUC of 0.941. Compared with existing methods, our set of miRNA functional similarity scores has higher reliability, larger coverage, and superior performance in prioritising disease-related miRNAs. We also conducted the case studies examining four common diseases and found that majority of the top ten candidates have been validated by experimental evidence.

Keywords: microRNAs; functional similarity; text mining; disease-related miRNA identification; biomedical texts; bioinformatics; diseases.

DOI: 10.1504/IJDMB.2016.077071

International Journal of Data Mining and Bioinformatics, 2016 Vol.15 No.3, pp.233 - 249

Accepted: 14 Mar 2016
Published online: 20 Jun 2016 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article