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      A Nextflow Pipeline for Network-Based Disease Module Identification and Validation

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            Abstract

            Content

            Author and article information

            Conference
            Publisher: REPO4EU
            Publication date (Electronic, pub): 19 July 2024
            Affiliations
            [1 ] Data Science in Systems Biology, TUM School of Life Sciences, Technical University of Munich, Munich, Germany ( https://ror.org/02kkvpp62)
            [2 ] Discovery and Data Science (DDS) Unit, STALICLA SL, Barcelona, Spain;
            [3 ] Max Perutz Labs, Vienna BioCenter Campus, Department of Structural and Computational Biology, University of Vienna, Vienna, Austria ( https://ror.org/03prydq77)
            [4 ] Ludwig Boltzmann Gesellschaft, Institute for Network Medicine, Vienna, Austria ( https://ror.org/01v1jam04)
            [5 ] Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany ( https://ror.org/00g30e956)
            Author notes
            Author information
            https://orcid.org/0000-0002-3882-0093
            https://orcid.org/0000-0002-5706-2718
            https://orcid.org/0000-0002-1971-1350
            https://orcid.org/0009-0004-0699-6475
            https://orcid.org/0009-0007-3502-3033
            https://orcid.org/0009-0007-4106-4659
            https://orcid.org/0000-0002-6171-1215
            https://orcid.org/0000-0001-7535-0417
            https://orcid.org/0000-0002-0282-0462
            https://orcid.org/0000-0002-1583-6404
            https://orcid.org/0000-0002-3466-6535
            https://orcid.org/0000-0002-0941-4168
            Article
            DOI: 10.58647/REXPO.24011
            SO-VID: 41319ae3-83d4-4f35-b345-6ada123fb68e
            Copyright © © 2024 The Authors
            License:

            Published under Creative Commons Attribution 4.0 International ( CC BY 4.0). Users are allowed to share (copy and redistribute the material in any medium or format) and adapt (remix, transform, and build upon the material for any purpose, even commercially), as long as the authors and the publisher are explicitly identified and properly acknowledged as the original source.

            Conference name: RExPO24
            Conference number: 3
            Conference location: Munich, Germany
            Conference date: 3-5 July 2024
            History
            Product

            REPO4EU

            Funding
            Funded by: funder-id http://dx.doi.org/10.13039/100018696, HORIZON EUROPE Health;
            Award ID: 101057619
            Categories

            Data availability: Data sharing not applicable to this article as no datasets were generated or analysed during the current study.
            ScienceOpen disciplines: Bioinformatics & Computational biology
            Keywords: disease modules,drug repurposing,pipeline,Nextflow,BioPAX,Docker,automatization,reproducibility

            References

            1. Levi Hagai, Elkon Ran, Shamir Ron. DOMINO: a network‐based active module identification algorithm with reduced rate of false calls. Molecular Systems Biology. Vol. 17(1)2021. Springer Science and Business Media LLC. [Cross Ref]

            2. Ghiassian Susan Dina, Menche Jörg, Barabási Albert-László. A DIseAse MOdule Detection (DIAMOnD) Algorithm Derived from a Systematic Analysis of Connectivity Patterns of Disease Proteins in the Human Interactome. PLOS Computational Biology. Vol. 11(4)2015. Public Library of Science (PLoS). [Cross Ref]

            3. Bernett Judith, Krupke Dominik, Sadegh Sepideh, Baumbach Jan, Fekete Sándor P, Kacprowski Tim, List Markus, Blumenthal David B. Robust disease module mining via enumeration of diverse prize-collecting Steiner trees. Bioinformatics. Vol. 38(6):1600–1606. 2022. Oxford University Press (OUP). [Cross Ref]

            4. Di Tommaso Paolo, Chatzou Maria, Floden Evan W, Barja Pablo Prieto, Palumbo Emilio, Notredame Cedric. Nextflow enables reproducible computational workflows. Nature Biotechnology. Vol. 35(4):316–319. 2017. Springer Science and Business Media LLC. [Cross Ref]

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