DNRLMF-MDA is one novel computational method, which utilizes comprehensive similarity measures and logistic matrix factorization algorithm to identify potential novel associations between miRNAs and diseases.

DataSet

The HMDD2.0-You dataset including disease functional similarity, disease sematic similarity and known miRNA-disease associations, is download obtained from the supplementary material of paper [You Z H, Huang Z A, Zhu Z, et al. PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction [J]. Plos Computational Biology, 2017, 13(3):e1005455.]. HMDD2.0-You.rar

The HMDD2.0-Wei dataset including disease functional similarity, disease sematic similarity and known miRNA-disease associations, is download obtained from the supplementary material of paper [Wei L, Wang J, Min L, et al. Predicting microRNA-disease associations based on improved microRNA and disease similarities[J]. IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2016, PP(99):1-1.].HMDD2.0-Wei.rar

The HMDD2.0-Cheng dataset including disease functional similarity, disease sematic similarity and known miRNA-disease associations, is download obtained from the HMDD database (http://cmbi.bjmu.edu.cn/hmdd).HMDD2.0-Cheng.rar

Scource code

1,Source code of DNRLMF-MDA algorithm can be downloaded here.
2,Readme.txt