Combined embedding model for MiRNA-disease association prediction.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: Cumulative evidence from biological experiments has confirmed that miRNAs have significant roles to diagnose and treat complex diseases. However, traditional medical experiments have limitations in time-consuming and high cost so that they fail to find the unconfirmed miRNA and disease interactions. Thus, discovering potential miRNA-disease associations will make a contribution to the decrease of the pathogenesis of diseases and benefit disease therapy. Although, existing methods using different computational algorithms have favorable performances to search for the potential miRNA-disease interactions. We still need to do some work to improve experimental results.

Authors

  • Bailong Liu
    Department of Radiation Oncology, The Second Affiliated Hospital of Anhui Medical University, 678 Furong Road, Hefei, Anhui, 230601, China.
  • Xiaoyan Zhu
    Anhui Technical College of Industry and Economy, Hefei, China.
  • Lei Zhang
    Division of Gastroenterology, Union Hospital, Tongji Medical College Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Zhizheng Liang
    School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, Jiangsu, China.
  • Zhengwei Li
    Engineering Research Center of Mine Digitalization of Ministry of Education, China University of Mining and Technology, Xuzhou, China. zwli@cumt.edu.cn.