RBMMMDA: predicting multiple types of disease-microRNA associations.
Accumulating evidences have shown that plenty of miRNAs play fundamental and important roles in various biological processes and the deregulations of miRNAs are associated with a broad range of human diseases. However, the mechanisms underlying the dysregulations of miRNAs still have not been fully understood yet. All the previous computational approaches can only predict binary associations between diseases and miRNAs. Predicting multiple types of disease-miRNA associations can further broaden our understanding about the molecular basis of diseases in the level of miRNAs. In this study, the model of Restricted Boltzmann machine for multiple types of miRNA-disease association prediction (RBMMMDA) was developed to predict four different types of miRNA-disease associations. Based on this model, we could obtain not only new miRNA-disease associations, but also corresponding association types. To our knowledge, RBMMMDA is the first model which could computationally infer association types of miRNA-disease pairs. Leave-one-out cross validation was implemented for RBMMMDA and the AUC of 0.8606 demonstrated the reliable and effective performance of RBMMMDA. In the case studies about lung cancer, breast cancer, and global prediction for all the diseases simultaneously, 50, 42, and 45 out of top 100 predicted miRNA-disease association types were confirmed by recent biological experimental literatures, respectively.
National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences, Beijing, 100190, China.|Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China.
Xing
X
Chen
Department of Automation, Tsinghua University, Beijing, 100084, China.
Chenggang Clarence
CC
Yan
School of Mechanical, Electrical &Information Engineering, Shandong University, Weihai, 264209, China.
Xiaotian
X
Zhang
School of Life Sciences, Tsinghua University, Beijing, 100084, China.|National Institute of Biological Sciences, Beijing, 102206, China.
Zhaohui
Z
Li
Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China.|University of Chinese Academy of Sciences, Beijing, 100049, China.
Lixi
L
Deng
Key Lab of Intelligent Information Processing of Chinese Academy of Sciences, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China.
Yongdong
Y
Zhang
Department of Automation, Tsinghua University, Beijing, 100084, China.
Qionghai
Q
Dai
D000465:Algorithms; D019295:Computational Biology / Q000379:methods; D056726:Genetic Association Studies / Q000379:methods*; D020022:Genetic Predisposition to Disease; D006801:Humans; D035683:MicroRNAs / Q000235:genetics*; D012372:ROC Curve; D015203:Reproducibility of Results; D012984:Software
D035683:MicroRNAs