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

Journal

Book Volume: 35

Article Number: btad345

Journal Issue: 6

DOI: 10.1093/bioinformatics/btad345

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.
Supplementary data are available at Bioinformatics online.

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How to cite

APA:

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). https://doi.org/10.1093/bioinformatics/btad345

MLA:

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

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