Introduction

MicroRNAs (miRNAs) are one class of important small non-coding RNA molecules and play critical roles in health and disease. It was reported that miRNAs can be clustered as functional sets, miRNAs with similar functions are often associated with similar diseases. It is important to quantify the functional relations among miRNAs and then build miRNA functional networks. Analyzing the functional similarity of miRNAs can help to understand the roles of miRNAs in many complex diseases such as cancer, cardiovascular and so on.

MISIM v2.0 is the updated web server of our previously published human microRNA functional similarity and functional network tool, MISIM (miRNA similarity http://www.cuilab.cn) in 2010. MISIM v2.0 is open-accessed and impoves the original MISIM algorithm by implementing both positive and negetive miRNA-disease associations. MISIM v2.0 is based on miRNA-disease data from the HMDD v3.0 database and the miRNA-disease data was curated using miRBase(Release 22.1). Currently, MISIM v2.0 contains 14250 miRNA-disease associations, including 1044 miRNAs and 613 diseases, and 547 miRNA sets from TAM 2.0.

MISIM v2.0 can offer the miRNA functional similarity in more details (e.g. stratifying by up and down-miRNAs) , higher quality and more accurate enrichment analysis to users. Moreover, MISIM v2.0 also can predict the novel association diseases for the interested miRNAs Finally, MSISM 2.0 is equipped with graphical visualization functions which make the server more user-friendly than previous version.

Quick start tutorial

Links

Groups

  • Dr. Jianwei Li
    Institute of Computational Medicine, School of Artificial Intelligence, Hebei University of Technology, Tianjin, China
    Email: lijianwei@hebut.edu.cn
  • Dr. Yuan Zhou
    Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University, Beijing, China
    Email: soontide6825@163.com
  • Dr. Qinghua Cui
    Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University, Beijing, China
    Email:cuiqinghua@hsc.pku.edu.cn
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