GreatMod seamlessly integrates Flux Balance Analysis (FBA) with dynamic Petri Net models to enable multi-scale modeling of biological systems. This powerful combination allows researchers to couple genome-scale metabolic networks with population-level dynamics.

What is FBA Integration?

The integration of Flux Balance Analysis (FBA) with Petri Net models creates a powerful multi-scale framework that bridges:

  • Genome-scale metabolic networks (constraint-based modeling via FBA)
  • Dynamic system behavior (ODEs and stochastic simulations via Petri Nets)

This approach allows you to:

  • Model metabolic reprogramming in response to environmental changes
  • Analyze host-pathogen metabolic interactions
  • Predict phenotypic behavior under different nutritional conditions
  • Couple intracellular metabolism with population dynamics

Examples

C. difficile Infection Model

C. difficile Model

Study of metabolic reprogramming during Clostridium difficile infection, including the acquisition of antibiotic-resistant phenotypes through heme supplementation.

View Example

E. coli Metabolic Modeling

E. coli Model

Integration of transcriptional data onto Escherichia coli genome-scale metabolic model (iML1515) growing on different regimes of carbon feeding.

View Example

epimod_FBAfunctions R Package

epimod_FBAfunctions

epimod_FBAfunctions Package

COBRA Model Processing: Read and modify COBRA MAT files, translate metabolic networks for epimod functions based on GLPK solver.

Sensitivity Analysis: Integrate Sobol's variance-based SA to classify reactions based on their impact on model outcomes.

View on GitHub

Reference

For more details on the FBA integration framework, please refer to our publication:

Riccardo Aucello, Simone Pernice, Dora Tortarolo, Raffaele A Calogero, Celia Herrera-Rincon, Giulia Ronchi, Stefano Geuna, Francesca Cordero, Pietro Lió, Marco Beccuti UnifiedGreatMod: a new holistic modelling paradigm for studying biological systems on a complete and harmonious scale, Bioinformatics, Volume 41, Issue 3, March 2025 https://doi.org/10.1093/bioinformatics/btaf103

Simone P, Laura F, et al.
Integrating Petri Nets and Flux Balance Methods in Computational Biology Models: a Methodological and Computational Practice. Fundamenta Informaticae. 2019;171(1-4):367-392. doi:10.3233/FI-2020-1888 https://journals.sagepub.com/doi/abs/10.3233/FI-2020-1888