Similarity computation strategies in the microRNA-disease network: a survey

Brief Funct Genomics. 2016 Jan;15(1):55-64. doi: 10.1093/bfgp/elv024. Epub 2015 Jul 1.

Abstract

Various microRNAs have been demonstrated to play roles in a number of human diseases. Several microRNA-disease network reconstruction methods have been used to describe the association from a systems biology perspective. The key problem for the network is the similarity computation model. In this article, we reviewed the main similarity computation methods and discussed these methods and future works. This survey may prompt and guide systems biology and bioinformatics researchers to build more perfect microRNA-disease associations and may make the network relationship clear for medical researchers.

Keywords: machine learning; microRNA; microRNA–disease relationship; network.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Algorithms*
  • Computational Biology / methods*
  • Disease / genetics*
  • Humans
  • Metabolic Networks and Pathways / genetics*
  • MicroRNAs / genetics*
  • Phenotype
  • Surveys and Questionnaires
  • Systems Biology

Substances

  • MicroRNAs