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A multi-objective genetic algorithm to find active modules in multiplex biological networks.

Elva María Novoa-Del-Toro1, Efrén Mezura-Montes2, Matthieu Vignes3

  • 1Aix Marseille Univ, INSERM, Marseille Medical Genetics (MMG), Marseille, France.

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|August 30, 2021
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Summary
This summary is machine-generated.

We developed MOGAMUN, a novel algorithm for identifying active modules in multiplex biological networks. This tool helps uncover perturbed cellular processes, offering new insights into diseases like muscular dystrophy.

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Area of Science:

  • Systems biology
  • Bioinformatics
  • Genomics

Background:

  • Identifying perturbed biological processes is crucial for understanding disease mechanisms.
  • Integrating molecular data with biological networks aids in pinpointing active cellular modules.
  • Existing methods often analyze single biological networks, limiting comprehensive analysis.

Purpose of the Study:

  • To introduce MOGAMUN, a Multi-Objective Genetic Algorithm for identifying active modules in multiplex biological networks.
  • To optimize module density and node scores (e.g., differential expression) simultaneously.
  • To leverage the diverse information present in multiplex networks for enhanced biological discovery.

Main Methods:

  • MOGAMUN employs a Multi-Objective Genetic Algorithm approach.
  • It optimizes for both interaction density within modules and node scores (e.g., differential gene expression).
  • The method is designed to analyze multiplex biological networks, integrating multiple layers of biological relationships.

Main Results:

  • MOGAMUN successfully identifies dense, high-scoring, and interpretable active modules.
  • It is the first method capable of utilizing multiplex biological networks for active module identification.
  • Application to Facio-Scapulo-Humeral muscular Dystrophy revealed key perturbed cellular processes and potential pathomechanisms.

Conclusions:

  • MOGAMUN provides a powerful new approach for identifying active modules in complex biological systems.
  • The ability to analyze multiplex networks offers a more holistic view of cellular perturbations.
  • This method facilitates deeper investigation into disease pathomechanisms, exemplified by its application to muscular dystrophy.