miRNA-Disease Association Prediction with Collaborative Matrix Factorization

Figure 2

Performance comparisons between CMFMDA and three state-of-the-art disease-miRNA association prediction models (NCPMDA, RLSMDA, and WBSMDA) in terms of ROC curve and AUC based on local and global LOOCV, respectively. As a result, CMFMDA achieved AUCs of 0.8841 and 0.8318 in the global and local LOOCV, significantly outperforming all the previous classical models.