Identification of Disease-miRNA Networks Across Different Cancer Types Using SWIM

MicroRNAs (miRNAs) are small noncoding RNAs (ncRNAs) involved in several biological processes anddiseases. MiRNAs regulate gene expression at the posttranscriptional level, mostly downregulating theirtargets by binding specific regions of transcripts through imperfect sequence complementarity. Predictionof miRNA-binding sites is challenging, and target prediction algorithms are usually based on sequencecomplementarity. In the last years, it has been shown that by adding miRNA and protein coding geneexpression, we are able to build tissue-, cell line-, or disease-specific networks improving our understandingof complex biological scenarios. In this chapter, we present an application of a recently published softwarenamed SWIM, that allows to identify key genes in a network of interactions by defining appropriate "roles"of genes according to their local/global positioning in the overall network. Furthermore, we show how theSWIM software can be used to build miRNA-disease networks, by applying the approach to tumor dataobtained from The Cancer Genome Atlas (TCGA).