Step 1: Input miRNA
Note:  This page accepts human miRNA genes (pre-miRNAs) as its input.
If the mature miRNA names (e.g. hsa-miR-140-5p) are provided, it will be collapsed into the corresponding miRNA gene (hsa-mir-140).
See sample example for details. 
sample example

   

Step 2:(optional)
If you not choose Up/Down Regulation, prediction miRNA disease association does not consider the UP and Down Regulation information.
Considering up/down-regulation in the similarity calculation

Step 3: Predict

Note: The weighted frequency value is obtained by the calculated miRNA functionality values.
For a given miRNA, MISIM v2.0 counts the number of prediction of a specific disease weighted by the miRNA functionality value.

miRNA Result
This website has been tested by using Chrome, Microsoft Edge and Firefox browsers. For better experience, please use Chrome and Firefox browsers.

If you use MISIM v2.0 in your work, please cite our publication:
Jianwei Li, Shan Zhang, Yanping Wan, Yingshu Zhao, Jiangcheng Shi, Yuan Zhou, and Qinghua Cui. MISIM v2.0: a web server for inferring microRNA functional similarity based on microRNA-disease associations.
Wang D, Wang, J, Lu M, Song F, and Cui Q. Inferring the human microRNA functional similarity and functional network based on microRNA-associated diseases. Bioinformatics 2010 26: 1644-1650. doi:10.1093/bioinformatics/btq241