Abstract: In order to quickly find out disease-related miRNAs， PMBP algorithm was proposed for improving random walk based on functional network information propagation. Leave-one-out cross validation was utilized to evaluate the performance of the algorithm and finally a case was analyzed. The results showed that random walk is ineffective for diseases that have not yet been associated with miRNAs， but the miRNA can be effectively predicted by using disease similarities as prior information. For the diseases known to be related with miRNAs， PMPB achieves a better performance and the corresponding AUC value is 0.866. In the case study of breast cancer， the predicted top 50 miRNAs are confirmed to be associated with breast cancer， which indicates the validity of PMBP.

Key words: functional network, disease network, network propagation, random walk, miRNA prediction