Circular RNAs (circRNAs) are a novel class of endogenous noncoding RNAs. Emerging evidence has shown that circRNAs can be novel biomarkers or therapeutic targets for many diseases. Therefore, identifying potential disease-related circRNAs is helpful in improving the efficiency of finding therapeutic targets for diseases. Here, a computational model (PreCDA) is proposed to predict potential circRNA-disease associations.
IDE：IntelliJ IDEA
Development Language: Java, scala
Note: please set the appropriate path before running
Step 1. run filehandler.java to create files that contains circRNA-disease associations from different circRNA databases
Step 2. run ExpressProfile.java to calculate circRNA expression similarity
Step 3. run circRNAsim.java to calculate circRNA functional similarity
Step 4. run UniNet.java to build the associations between circRNAs
Step 5. run PersonalRank.java to rank candidate circRNAs
Step 6. run TestSet.java to output the AUC value of predicting candidate disease-related circRNAs