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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.
Affiliation
  • Sarkar S; Biomedical Network Science Lab, Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen 91301, Germany.
  • Lucchetta M; Department of Experimental Oncology, IEO European Institute of Oncology IRCCS, Milan 20139, Italy.
  • Maier A; Institute for Computational Systems Biology, University of Hamburg, Hamburg 22607, Germany.
  • Abdrabbou MM; Biomedical Network Science Lab, Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen 91301, Germany.
  • Baumbach J; Institute for Computational Systems Biology, University of Hamburg, Hamburg 22607, Germany.
  • List M; Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Freising 85354, Germany.
  • Schaefer MH; Department of Experimental Oncology, IEO European Institute of Oncology IRCCS, Milan 20139, Italy.
  • Blumenthal DB; Biomedical Network Science Lab, Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen 91301, Germany.
Bioinformatics ; 39(6)2023 06 01.
Article in En | MEDLINE | ID: mdl-37233198
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.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Software Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2023 Type: Article Affiliation country: Germany

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Software Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2023 Type: Article Affiliation country: Germany