Predicting microRNA-disease associations from lncRNA-microRNA interactions via Multiview Multitask Learning.

Journal: Briefings in bioinformatics
Published Date:

Abstract

MOTIVATION: Identifying microRNAs that are associated with different diseases as biomarkers is a problem of great medical significance. Existing computational methods for uncovering such microRNA-diseases associations (MDAs) are mostly developed under the assumption that similar microRNAs tend to associate with similar diseases. Since such an assumption is not always valid, these methods may not always be applicable to all kinds of MDAs. Considering that the relationship between long noncoding RNA (lncRNA) and different diseases and the co-regulation relationships between the biological functions of lncRNA and microRNA have been established, we propose here a multiview multitask method to make use of the known lncRNA-microRNA interaction to predict MDAs on a large scale. The investigation is performed in the absence of complete information of microRNAs and any similarity measurement for it and to the best knowledge, the work represents the first ever attempt to discover MDAs based on lncRNA-microRNA interactions.

Authors

  • Yu-An Huang
    Department of Computing, Hong Kong Polytechnic University, Hung Hom, Hong Kong, China.
  • Keith C C Chan
    Department of Computing, Hong Kong Polytechnic University, Hong Kong.
  • Zhu-Hong You
    Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Urumqi, 830011, China. zhuhongyou@ms.xjb.ac.cn.
  • Pengwei Hu
    The Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Ürümqi, China.
  • Lei Wang
    Department of Nursing, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
  • Zhi-An Huang
    City University of Hong Kong.