experimentally verified miRNA-disease associations to compute the functional similarity score between every two Zarnestra miRNAs associated with the same disease, and obtained a ROC curve as the methods described in our analysis. Finally, the method presented by Yu et al. achieved an AUC of 63.9, but is less than an AUC of 83.1 obtained by our miRFunSim method tested on the same datasets. Taken together, these results suggested that our miRFunSim method can achieve more effective and more reliable performance for quantifying the associations between miRNAs compared with other available similar methods. As an example, to illustrate the application of quantifying the relationship between miRNAs using miRFunSim method, we presented a case study of liver cancer, which is one of the most common cancers, and applied the miRFunSim method to identify novel candidate liver cancer-related miRNAs. First, we retrieved 15 miRNAs which have been experimentally verified to contribute to the development of liver cancer and have experimentally verified target genes in TarBase as seed miRNAs. Next, we computed the functional similarity scores between every seed miRNAs and every miRNA from the remaining 85 miRNAs using miRFunSim method. The higher the score is, the more likely the miRNAs is associated with liver cancer. Finally, we prioritized all 1275 miRNA pairs for liver cancer according to their scores. The top 15 miRNA pairs with the highest functional similarity scores were chosen and 12 miRNAs with the highest functional similarity scores with seed miRNAs were listed as candidate liver cancer-related miRNAs and shown in Table 1. Among top 12 miRNAs, 8 miRNAs have been recorded to be deregulated in liver cancer and 1439901-97-9 possibly contribute to the development of liver cancer, and 4 miRNAs have been verified to be deregulated in other cancers in miR2Disease, and PhenomiR databases which provide comprehensive resources for miRNA deregulation in disease. When our research is in progress, a new study provided further supporting evidence for one of the remaining four candidate liver cancer-related miRNAs. Li et al. found that miR-34 participate in the neoplastic transformation of liver cancer
