Predicting miRNA-based disease-disease relationships through network diffusion on multi-omics biological data.

ABSTRACT: With critical roles in regulating gene expression, miRNAs are strongly implicated in the pathophysiology of many complex diseases. Experimental methods to determine disease related miRNAs are time consuming and costly. Computationally predicting miRNA-disease associations has potential applications in finding miRNA therapeutic pathways and in understanding the role of miRNAs in disease-disease relationships. In this study, we propose the MiRNA-disease Association Prediction (MAP) method, an in-silico method to predict and prioritize miRNA-disease associations. The MAP method applies a network diffusion approach, starting from the known disease genes in a heterogenous network constructed from miRNA-gene associations, protein-protein interactions, and gene-disease associations. Validation us

SUBMITTER: Sumathipala M 

PROVIDER: S-EPMC7251138 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature