DiCE-Ex: a web server for network-based differential-centrality gene exploration

Identifying condition-specific disease drivers from transcriptomic data requires analytical frameworks that capture not only differential expression but also dynamic changes in network organization. Many existing approaches treat genes as independent features or rely primarily on co-expression similarity and hub identification, which can miss context-dependent regulators that drive network rewiring within protein-protein interaction (PPI) networks. To address these limitations, we present a web server DiCE-Ex (Differential Centrality-Ensemble Exploration) designed to prioritize genes whose network roles and topological influence are rewired between conditions, even though some of them may not exhibit large expression changes. DiCE-Ex integrates gene expression data with PPI networks to construct condition-specific weighted interaction networks and systematically evaluates centrality shifts across an ensemble of network measures selected by the user. By focusing on changes in network centrality rather than expression magnitude alone, DiCE-Ex identifies genes that act as key mediators of condition-dependent signalling and regulatory reorganization. Case studies demonstrate that DiCE-Ex successfully recovers known disease modulators while also identifying key nonhub regulators that are overlooked by conventional differential expression analyses, thereby highlighting strong candidates for mechanistic validation and therapeutic development. DiCE-Ex is freely available at https://connect.posit.iu.edu/DiCE-Ex/ with example datasets, comprehensive documents, step-by-step tutorials, and shareable job permalinks.