MDA-SKF: Similarity Kernel Fusion for Accurately Discovering miRNA-Disease Association.

ABSTRACT: Identifying accurate associations between miRNAs and diseases is beneficial for diagnosis and treatment of human diseases. It is especially important to develop an efficient method to detect the association between miRNA and disease. Traditional experimental method has high precision, but its process is complicated and time-consuming. Various computational methods have been developed to uncover potential associations based on an assumption that similar miRNAs are always related to similar diseases. In this paper, we propose an accurate method, MDA-SKF, to uncover potential miRNA-disease associations. We first extract three miRNA similarity kernels (miRNA functional similarity, miRNA sequence similarity, Hamming profile similarity for miRNA) and three disease similarity kernels (disease sem

SUBMITTER: Jiang L 

PROVIDER: S-EPMC6295467 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature