GCSENet: A GCN, CNN and SENet ensemble model for microRNA-disease association prediction.

ABSTRACT: Recently, an increasing number of studies have demonstrated that miRNAs are involved in human diseases, indicating that miRNAs might be a potential pathogenic factor for various diseases. Therefore, figuring out the relationship between miRNAs and diseases plays a critical role in not only the development of new drugs, but also the formulation of individualized diagnosis and treatment. As the prediction of miRNA-disease association via biological experiments is expensive and time-consuming, computational methods have a positive effect on revealing the association. In this study, a novel prediction model integrating GCN, CNN and Squeeze-and-Excitation Networks (GCSENet) was constructed for the identification of miRNA-disease association. The model first captured features by GCN based on a h

SUBMITTER: Li Z 

PROVIDER: S-EPMC8205154 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature