Author, as appears in the article.: Tomasoni, Mattia; Gomez, Sergio; Crawford, Jake; Zhang, Weijia; Choobdar, Sarvenaz; Marbach, Daniel; Bergmann, Sven
Department: Enginyeria Informàtica i Matemàtiques
URV's Author/s: Gómez Jiménez, Sergio
Keywords: Software Community structure Algorithms
Abstract: © The Author(s) 2020. Published by Oxford University Press. SUMMARY: 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. AVAILABILITY AND IMPLEMENTATION: 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 INFORMATION: Supplementary data are available at Bioinformatics online.
Thematic Areas: Statistics and probability Statistics & probability Odontología Nutrição Molecular biology Medicina veterinaria Medicina ii Medicina i Mathematics, interdisciplinary applications Mathematical & computational biology Matemática / probabilidade e estatística Interdisciplinar General medicine Engenharias iv Economia Computer science, interdisciplinary applications Computer science applications Computational theory and mathematics Computational mathematics Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências agrárias i Ciência da computação Biotecnología Biotechnology & applied microbiology Biology, miscellaneous Biodiversidade Biochemistry Biochemical research methods Astronomia / física
licence for use: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 1367-4803
Author's mail: sergio.gomez@urv.cat
Author identifier: 0000-0003-1820-0062
Last page: 3921
Record's date: 2024-10-26
Journal volume: 36
Papper version: info:eu-repo/semantics/publishedVersion
Link to the original source: https://academic.oup.com/bioinformatics/article/36/12/3920/5818484
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Bioinformatics. 36 (12): 3920-3921
APA: Tomasoni, Mattia; Gomez, Sergio; Crawford, Jake; Zhang, Weijia; Choobdar, Sarvenaz; Marbach, Daniel; Bergmann, Sven (2020). MONET: a toolbox integrating top-performing methods for network modularization. Bioinformatics, 36(12), 3920-3921. DOI: 10.1093/bioinformatics/btaa236
Article's DOI: 10.1093/bioinformatics/btaa236
Entity: Universitat Rovira i Virgili
Journal publication year: 2020
First page: 3920
Publication Type: Journal Publications
Repositori URV