In Silico Prediction of Small Molecule-miRNA Associations Based on the HeteSim Algorithm.

ABSTRACT: Targeting microRNAs (miRNAs) with drug small molecules (SMs) is a new treatment method for many human complex diseases. Unsurprisingly, identification of potential miRNA-SM associations is helpful for pharmaceutical engineering and disease therapy in the field of medical research. In this paper, we developed a novel computational model of HeteSim-based inference for SM-miRNA Association prediction (HSSMMA) by implementing a path-based measurement method of HeteSim on a heterogeneous network combined with known miRNA-SM associations, integrated miRNA similarity, and integrated SM similarity. Through considering paths from an SM to a miRNA in the heterogeneous network, the model can capture the semantics information under each path and predict potential miRNA-SM associations based on all the

SUBMITTER: Qu J 

PROVIDER: S-EPMC6348698 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature