An approach for prioritizing disease-related microRNAs based on genomic data integration

The identification of disease microRNAs is vital for understanding the pathogenesis of diseases at the molecular level, and is critical for designing specific molecular tools for diagnosis, treatment and prevention. However, one major issue in microRNA studies is the lack of bioinformatics methods to accurately predict disease-related microRNAs. Herein, we proposed an approach for prioritizing disease-related microRNAs based on genomic data integration. We applied our method to colon cancer and verified the effectiveness of the method. The method described here presents a promising approach to prioritizing disease-related microRNAs, which will provide leads for further experimental investigation.