MONET: a toolbox integrating top-performing methods for network modularization.


Journal

Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944

Informations de publication

Date de publication:
01 06 2020
Historique:
received: 12 12 2019
revised: 09 03 2020
accepted: 02 04 2020
pubmed: 10 4 2020
medline: 29 12 2020
entrez: 10 4 2020
Statut: ppublish

Résumé

We define a disease module as a partition of a molecular network whose components are jointly associated with one or several diseases or risk factors thereof. Identification of such modules, across different types of networks, has great potential for elucidating disease mechanisms and establishing new powerful biomarkers. To this end, we launched the 'Disease Module Identification (DMI) DREAM Challenge', a community effort to build and evaluate unsupervised molecular network modularization algorithms. Here, we present MONET, a toolbox providing easy and unified access to the three top-performing methods from the DMI DREAM Challenge for the bioinformatics community. MONET is a command line tool for Linux, based on Docker and Singularity containers; the core algorithms were written in R, Python, Ada and C++. It is freely available for download at https://github.com/BergmannLab/MONET.git. Supplementary data are available at Bioinformatics online.

Identifiants

pubmed: 32271874
pii: 5818484
doi: 10.1093/bioinformatics/btaa236
pmc: PMC7320625
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3920-3921

Informations de copyright

© The Author(s) 2020. Published by Oxford University Press.

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Auteurs

Mattia Tomasoni (M)

Department of Computational Biology, University of Lausanne.
Swiss Institute of Bioinformatics, Lausanne, Switzerland.

Sergio Gómez (S)

Departament d'Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, Tarragona, Catalonia, Spain.

Jake Crawford (J)

Department of Computer Science, Tufts University, MA.
Graduate Group in Genomics and Computational Biology Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.

Weijia Zhang (W)

School of Information Technology and Mathematical Sciences, University of South Australia, Adelaide, Australia.

Sarvenaz Choobdar (S)

Department of Computational Biology, University of Lausanne.
Swiss Institute of Bioinformatics, Lausanne, Switzerland.

Daniel Marbach (D)

Department of Computational Biology, University of Lausanne.
Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, 4070 Basel, Switzerland.

Sven Bergmann (S)

Department of Computational Biology, University of Lausanne.
Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa.

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Classifications MeSH