PMAMCA: prediction of microRNA-disease association utilizing a matrix completion approach.

ABSTRACT: BACKGROUND:Numerous experimental results have indicated that microRNAs (miRNAs) play a vital role in biological processes, as well as outbreaks of diseases at the molecular level. Despite their important role in biological processes, knowledge regarding specific functions of miRNAs in the development of human diseases is very limited. While attempting to solve this problem, many computational approaches have been proposed and attracted significant attention. However, most previous approaches suffer from the common problem of being inapplicable to new diseases without any known miRNA-disease associations. RESULTS:This paper proposes a novel method for inferring disease-miRNA associations utilizing a machine learning technique called matrix factorization, which is widely used in recommendati

SUBMITTER: Ha J 

PROVIDER: S-EPMC6425656 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature