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Maboss for HPC environments: implementations of the continuous time Boolean model simulator for large CPU clusters

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New computational tools, MaBoSS.MPI and MaBoSS.GPU, enhance Boolean modeling for systems biology. These simulators accelerate the analysis of large-scale biological networks, advancing mechanistic understanding of phenotypes.

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Area of Science:

  • Systems Biology
  • Computational Biology
  • Bioinformatics

Background:

  • Computational models are crucial for understanding complex biological systems and phenotypes.
  • Boolean models effectively represent signaling networks and scale to many components.
  • Advancements in Boolean model inference necessitate scalable simulation software.

Purpose of the Study:

  • To adapt simulation software for increasingly complex and large-scale Boolean models in systems biology.
  • To enhance the computational efficiency of Boolean model simulations.

Main Methods:

  • Development of MaBoSS.MPI, a parallel implementation of the MaBoSS simulator for CPU clusters.
  • Development of MaBoSS.GPU, utilizing GPU accelerators for Boolean simulations.

Main Results:

  • MaBoSS.MPI enables exploitation of computational power from large CPU clusters.
  • MaBoSS.GPU leverages GPU accelerators for efficient simulation.
  • Both developments significantly increase the capacity for simulating large Boolean models.

Conclusions:

  • The new MaBoSS implementations are valuable tools for simulating and exploring very large biological models.
  • These advancements facilitate deeper mechanistic analysis in systems biology.
  • The tools support the growing need for analyzing complex, automatized Boolean models.