Figure 1
From: Triple negative aggressive phenotype controlled by miR-135b and miR-365: new theranostics candidates
Overview of the data, methods (a) and results (b) for TBNC network identification (A) Workflow of the proposed computational approach. It consists of 6 steps. (1) identification of differentially expressed genes (DEGs) between basal and normal samples from TCGA data, (2) pathway enrichment analysis. In this step we identified the pathways enriched with DEGs, (3) construction of a classifier to distinguish basal versus normal samples using a metric able to reveal the interactions among pathways, (4) the classifier was evaluated using Area Under Curve (AUC) in the training and testing test, (5) we selected the pairs of pathways that achieved the best AUC values, (6) we applied an integration algorithm between miRNA and pathway in order to identify miRNAs regulating pathway network in basal breast cancer. (B) miRNAs regulating pathway network. The figure shows the top 10 pairs of pathways that achieved the best performance in the classification of basal versus normal samples and miRNAs regulating this network.
