NORDic is an open-source package designed for network-based transcriptional analysis for drug repurposing, (1) enabling the inference of disease-specific gene regulatory networks, (2) identifying key genes in the regulation (master regulators), (3) simulating in silico the drug effect in pathological profiles, and (4) screening automatically drugs based on those simulations. This demo applies two functionalities of NORDic to proteome and transcriptome datasets from resilient and post-traumatic stress disorder (PTSD)- diagnosed individuals. Indeed, PTSD is associated with widespread protein and gene dysregulations in blood and across multiple brain regions [1,2]. However, traditional differential expression analyses often fail to capture the complex interactions between groups of genes governing these molecular changes. Here, the aim is to model a gene regulatory network predictive of PTSD risk and to identify master regulators of resilience to PTSD. We start this demo with the Network Identification (NI) function, that builds a dynamic regulatory model (a boolean network) by integrating input and publicly available biological sources in an automated fashion. Then, we apply the Prioritization of Master Regulators (PMR) function. This function identifies disease-specific master regulators based on the topology and dynamics of the network, redefining gene centrality as the primary target to drive pathological transcriptional profiles toward resilient ones. Future extensions will explore the integration of other omic layers (e.g., microRNAs, DNA methylation) to refine disease models further.