The use of genome-wide, sample-matched miRNA (miRNAs)-mRNA expression data provides a powerful tool for the investigation of miRNAs and genes involved in diseases. The identification of miRNA-regulated pathways has been crucial for analysis of the role of miRNAs. However, the classical identification method fails to consider the structural information of pathways and the regulation of miRNAs simultaneously. We proposed a method that simultaneously integrated the change in gene expression and structural information in order to identify pathways. Our method used fold changes in miRNAs and gene products, along with the quantification of the regulatory effect on target genes, to measure the change in gene expression. Topological characteristics were investigated to measure the influence of gene products on entire pathways. Through the analysis of multiple myeloma and prostate cancer expression data, our method was proven to be effective and reliable in identifying disease risk pathways that are regulated by miRNAs. Further analysis showed that the structure of a pathway plays a crucial role in the recognition of the pathway as a factor in disease risk. 
The detection of risk pathways, regulated by miRNAs, via the integration of sample-matched miRNA-mRNA profiles and pathway structure