WBNPMD: weighted bipartite network projection for microRNA-disease association prediction.

ABSTRACT: BACKGROUND:Recently, numerous biological experiments have indicated that microRNAs (miRNAs) play critical roles in exploring the pathogenesis of various human diseases. Since traditional experimental methods for miRNA-disease associations detection are costly and time-consuming, it becomes urgent to design efficient and robust computational techniques for identifying undiscovered interactions. METHODS:In this paper, we proposed a computation framework named weighted bipartite network projection for miRNA-disease association prediction (WBNPMD). In this method, transfer weights were constructed by combining the known miRNA and disease similarities, and the initial information was properly configured. Then the two-step bipartite network algorithm was implemented to infer potential miRNA-dise

SUBMITTER: Xie G 

PROVIDER: S-EPMC6757419 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature