标题：HAMDA: Hybrid Approach for MiRNA-Disease Association prediction
作者：Chen, Xing; Niu, Ya-Wei; Wang, Guang-Hui; Yan, Gui-Ying
作者机构：[Chen, Xing] China Univ Min & Technol, Sch Informat & Control Engn, Xuzhou 221116, Peoples R China.; [Niu, Ya-Wei; Wang, Guang-Hui] Shandong Univ, S 更多
通讯作者地址：[Chen, X]China Univ Min & Technol, Sch Informat & Control Engn, Xuzhou 221116, Peoples R China;[Wang, GH]Shandong Univ, Sch Math, Jinan 250100, Shando 更多
来源：JOURNAL OF BIOMEDICAL INFORMATICS
关键词：miRNA; Disease; miRNA-disease association; Hybrid prediction approach;; Recommendation systems
摘要：For decades, enormous experimental researches have collectively indicated that microRNA (miRNA) could play indispensable roles in many critical biological processes and thus also the pathogenesis of human complex diseases. Whereas the resource and time cost required in traditional biology experiments are expensive, more and more attentions have been paid to the development of effective and feasible computational methods for predicting potential associations between disease and miRNA. In this study, we developed a computational model of Hybrid Approach for MiRNA-Disease Association prediction (HAMDA), which involved the hybrid graph-based recommendation algorithm, to reveal novel miRNA-disease associations by integrating experimentally verified miRNA-disease associations, disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity into a recommendation algorithm. HAMDA took not only network structure and information propagation but also node attribution into consideration, resulting in a satisfactory prediction performance. Specifically, HAMDA obtained AUCs of 0.9035 and 0.8395 in the frameworks of global and local leave-one-out cross validation, respectively. Meanwhile, HAMDA also achieved good performance with AUC of 0.8965 +/- 0.0012 in 5-fold cross validation. Additionally, we conducted case studies about three important human cancers for performance evaluation of HAMDA. As a result, 90% (Lymphoma), 86% (Prostate Cancer) and 92% (Kidney Cancer) of top 50 predicted miRNAs were confirmed by recent experiment literature, which showed the reliable prediction ability of HAMDA.