A network embedding-based multiple information integration method for the MiRNA-disease association prediction.

ABSTRACT:

Background

MiRNAs play significant roles in many fundamental and important biological processes, and predicting potential miRNA-disease associations makes contributions to understanding the molecular mechanism of human diseases. Existing state-of-the-art methods make use of miRNA-target associations, miRNA-family associations, miRNA functional similarity, disease semantic similarity and known miRNA-disease associations, but the known miRNA-disease associations are not well exploited.

Results

In this paper, a network embedding-based multiple information integration method (NEMII) is proposed for the miRNA-disease association prediction. First, known miRNA-disease associations are formulated as a bipartite network, and the network embedding method Structural Deep Network Embed

SUBMITTER: Gong Y 

PROVIDER: S-EPMC6740005 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature