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
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
3920-3921Informations de copyright
© The Author(s) 2020. Published by Oxford University Press.
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