This web server provides a method to infer potential interaction between microRNA and disease for further confirmation using biological experiments. First, we use MeSH tree structure and disease related genes to measure the disease similarity, and the subnetwork of microRNA similarity is constructed using the microRNA–target gene and microRNA-long non-coding RNA associations. A heterogeneous network was constructed by connecting the disease similarity subnetwork and the microRNA similarity subnetwork using the experimentally verified microRNA–disease associations. We extend the framework of random walk with restart to predict microRNA–disease associations in the heterogeneous network.


  1. Leave-one-out cross-validation

    The area under the curve (AUC) is 0.8049.

  2. Five-fold cross-validation

    For 15 human diseases, an AUC from 0.7970 to 0.9249.

  3. Application to disease with no known related microRNAs

  4. Cases studies: lung neoplasms and breast neoplasms

The data sources

HMDDhuman microRNA-disease database
MeSHMedical Subject Headings
DisGeNETa database of gene-disease associations
miRTarBaseexperimentally validated microRNA-target gene interactions
starBase v2.0microRNA-lncRNA interactions
LncRNADiseasethe experimentally supported lncRNA-disease association
HumanNeta probabilistic functional gene network