A Novel Neighborhood-Based Computational Model for Potential MiRNA-Disease Association Prediction.

ABSTRACT: In recent years, more and more studies have shown that miRNAs can affect a variety of biological processes. It is important for disease prevention, treatment, diagnosis, and prognosis to study the relationships between human diseases and miRNAs. However, traditional experimental methods are time-consuming and labour-intensive. Hence, in this paper, a novel neighborhood-based computational model called NBMDA is proposed for predicting potential miRNA-disease associations. Due to the fact that known miRNA-disease associations are very rare and many diseases (or miRNAs) are associated with only one or a few miRNAs (or diseases), in NBMDA, the K-nearest neighbor (KNN) method is utilized as a recommendation algorithm based on known miRNA-disease associations, miRNA functional similarity,

SUBMITTER: Liu Y 

PROVIDER: S-EPMC6360053 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature