A New System for Human MicroRNA functional Evaluation and Network

MicroRNAs are functionally important endogenous non-coding RNAs that silence host genes in animal and plant via destabilizing the mRNAs or preventing the translation. Given the far-reaching implication of microRNA regulation in human health, novel bioinformatics tools are desired to facilitate the mechanistic understanding of microRNA mediated gene regulation, their roles in biological processes, and the functional relevance among microRNAs. However, most state-of-the-art computational methods still focus on the functional study of microRNA targets and there is no e ective strategy to infer the functional similarity among microRNAs. In this study, we developed a new method to quantitatively measure the functional similarity among microRNAs based on the integrated functional annotation data from Gene Ontology, human pathways, and PFam databases. Through analyzing human microRNAs, we further demonstrated the use of the derived microRNA pairwise similarities to discover the cooperative microRNA modules and to construct the genome-scale microRNAmediated gene network in human. The complete results and the similarity assessment system can be freely accessed at (http://sbbi.unl.edu/microRNASim). Adviser: Juan Cu