Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

A Multi-Objective Genetic Algorithm to Find Active Modules in Multiplex Biological Networks

Elva-María Novoa-del-Toro, Efrén Mezura-Montes, Matthieu Vignes, Frédérique Magdinier, Laurent Tichit, Anaïs Baudot
doi: https://doi.org/10.1101/2020.05.25.114215
Elva-María Novoa-del-Toro
1Aix Marseille Univ, INSERM, Marseille Medical Genetics (MMG), Marseille, France
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: anais.baudot@univ-amu.fr
Efrén Mezura-Montes
2University of Veracruz, Artificial Intelligence Research Center, Mexico
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Matthieu Vignes
3School of Fundamental Sciences, Massey University, New Zealand
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Frédérique Magdinier
1Aix Marseille Univ, INSERM, Marseille Medical Genetics (MMG), Marseille, France
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Laurent Tichit
4Aix Marseille Univ, CNRS, Centale Marseille, I2M UMR 7373, Marseille, France
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Anaïs Baudot
1Aix Marseille Univ, INSERM, Marseille Medical Genetics (MMG), Marseille, France
5Barcelona Supercomputing Center, Barcelona 08034, Spain
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: anais.baudot@univ-amu.fr
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

The identification of subnetworks of interest - or active modules - by integrating biological networks with molecular profiles is a key resource to inform on the processes perturbed in different cellular conditions. We here propose MOGAMUN, a Multi-Objective Genetic Algorithm to identify active modules in multiplex biological networks. MOGAMUN optimizes both the density of interactions and the scores of the nodes (e.g., their differential expression).

We compare MOGAMUN with state-of-the-art methods, representative of different algorithms dedicated to the identification of active modules in single networks. MOGAMUN identifies dense and high-scoring modules that are also easier to interpret. In addition, to our knowledge, MOGAMUN is the first method able to use multiplex networks. Multiplex networks are composed of different layers of physical and functional relationships between genes and proteins. Each layer is associated to its own meaning, topology, and biases; the multiplex framework allows exploiting this diversity of biological networks.

We applied MOGAMUN to identify cellular processes perturbed in Facio-Scapulo-Humeral muscular Dystrophy, by integrating RNA-seq expression data with a multiplex biological network. We identified different active modules of interest, thereby providing new angles for investigating the pathomechanisms of this disease.

Availability MOGAMUN is available at https://github.com/elvanov/MOGAMUN.

Contact elva.novoa{at}inserm.fr, anais.baudot{at}univ-amu.fr

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted May 26, 2020.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
A Multi-Objective Genetic Algorithm to Find Active Modules in Multiplex Biological Networks
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
A Multi-Objective Genetic Algorithm to Find Active Modules in Multiplex Biological Networks
Elva-María Novoa-del-Toro, Efrén Mezura-Montes, Matthieu Vignes, Frédérique Magdinier, Laurent Tichit, Anaïs Baudot
bioRxiv 2020.05.25.114215; doi: https://doi.org/10.1101/2020.05.25.114215
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
A Multi-Objective Genetic Algorithm to Find Active Modules in Multiplex Biological Networks
Elva-María Novoa-del-Toro, Efrén Mezura-Montes, Matthieu Vignes, Frédérique Magdinier, Laurent Tichit, Anaïs Baudot
bioRxiv 2020.05.25.114215; doi: https://doi.org/10.1101/2020.05.25.114215

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Systems Biology
Subject Areas
All Articles
  • Animal Behavior and Cognition (4383)
  • Biochemistry (9599)
  • Bioengineering (7094)
  • Bioinformatics (24865)
  • Biophysics (12615)
  • Cancer Biology (9958)
  • Cell Biology (14354)
  • Clinical Trials (138)
  • Developmental Biology (7950)
  • Ecology (12107)
  • Epidemiology (2067)
  • Evolutionary Biology (15989)
  • Genetics (10925)
  • Genomics (14743)
  • Immunology (9870)
  • Microbiology (23676)
  • Molecular Biology (9485)
  • Neuroscience (50872)
  • Paleontology (369)
  • Pathology (1539)
  • Pharmacology and Toxicology (2683)
  • Physiology (4016)
  • Plant Biology (8657)
  • Scientific Communication and Education (1509)
  • Synthetic Biology (2397)
  • Systems Biology (6436)
  • Zoology (1346)