SSCMDA: spy and super cluster strategy for MiRNA-disease association prediction.

ABSTRACT: In the biological field, the identification of the associations between microRNAs (miRNAs) and diseases has been paid increasing attention as an extremely meaningful study for the clinical medicine. However, it is expensive and time-consuming to confirm miRNA-disease associations by experimental methods. Therefore, in recent years, several effective computational models for predicting the potential miRNA-disease associations have been developed. In this paper, we proposed the Spy and Super Cluster strategy for MiRNA-Disease Association prediction (SSCMDA) based on known miRNA-disease associations, integrated disease similarity and integrated miRNA similarity. For problems of mixed unknown miRNA-disease pairs containing both potential associations and real negative associations, which will

SUBMITTER: Zhao Q 

PROVIDER: S-EPMC5788602 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature