Online bias-aware disease module mining with ROBUST-Web - Sarkar, Suryadipto; Lucchetta, Marta; Maier, Andreas; Abdrabbou, Mohamed M; Baumbach, Jan; List, Markus; Schaefer, Martin H; Blumenthal, David B (Bioinformatics (Oxford, England), 2023)
Abstract Summary We present ROBUST-Web which implements our recently presented ROBUST disease module mining algorithm in a user-friendly web application. ROBUST-Web features seamless downstream disease module exploration via integrated gene set enrichment analysis, tissue expression annotation, and visualization of drug–protein and disease–gene links. Moreover, ROBUST-Web includes bias-aware edge costs for the underlying Steiner tree model as a new algorithmic feature, which allow to correct for study bias in protein–protein interaction networks and further improves the robustness of the computed modules. Availability and implementation Web application: https://robust-web.net. Source code of web application and Python package with new bias-aware edge costs: https://github.com/bionetslab/robust-web, https://github.com/bionetslab/robust_bias_aware.