Online bias-aware disease module mining with ROBUST-Web

Sarkar S, Lucchetta M, Maier A, Abdrabbou MMM, Baumbach J, List M, Schaefer MH, Blumenthal DB (2023)

Publication Language: English

Publication Status: Published

Publication Type: Journal article

Publication year: 2023


Book Volume: 35

Article Number: btad345

Journal Issue: 6

DOI: 10.1093/bioinformatics/btad345



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: Source code of web application and Python package with new bias-aware edge costs:,
Supplementary data are available at Bioinformatics online.

Authors with CRIS profile

Involved external institutions

How to cite


Sarkar, S., Lucchetta, M., Maier, A., Abdrabbou, M.M.M., Baumbach, J., List, M.,... Blumenthal, D.B. (2023). Online bias-aware disease module mining with ROBUST-Web. Bioinformatics, 35(6).


Sarkar, Suryadipto, et al. "Online bias-aware disease module mining with ROBUST-Web." Bioinformatics 35.6 (2023).

BibTeX: Download