ArticlePLoS computational biology2021
MASSpy: Building, simulating, and visualizing dynamic biological models in Python using mass action kinetics.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Machine learning and data-driven inverse modeling of metabolomics unveil key processes of active aging.NPJ systems biology and applications · 2025Trial
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- Generative approaches to kinetic parameter inference in metabolic networks via latent space exploration.Nature communications · 2026Article
- The Dawn of High-Throughput and Genome-Scale Kinetic Modeling: Recent Advances and Future Directions.ACS synthetic biology · 2025Review
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- RBC-GEM: A genome-scale metabolic model for systems biology of the human red blood cell.PLoS computational biology · 2025Article
- The Constrained Disorder Principle Overcomes the Challenges of Methods for Assessing Uncertainty in Biological Systems.Journal of personalized medicine · 2024Review
- Network structure and fluctuation data improve inference of metabolic interaction strengths with the inverse Jacobian.NPJ systems biology and applications · 2024Article
- Biological and genetic determinants of glycolysis: Phosphofructokinase isoforms boost energy status of stored red blood cells and transfusion outcomes.Cell metabolism · 2024Article
- Learning metabolic dynamics from irregular observations by Bidirectional Time-Series State Transfer Network.mSystems · 2024Article
- Bottom-up parameterization of enzyme rate constants: Reconciling inconsistent data.Metabolic engineering communications · 2024Article
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- Rational strain design with minimal phenotype perturbation.Nature communications · 2024Article
- Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states.Nature catalysis · 2024Article
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- VSCode-Antimony: a source editor for building, analyzing, and translating antimony models.Bioinformatics (Oxford, England) · 2023Article
- Modeling Red Blood Cell Metabolism in the Omics Era.Metabolites · 2023Review
- Catalyst: Fast and flexible modeling of reaction networks.PLoS computational biology · 2023Article
- Optimal enzyme utilization suggests that concentrations and thermodynamics determine binding mechanisms and enzyme saturations.Nature communications · 2023Article
- libRoadRunner 2.0: a high performance SBML simulation and analysis library.Bioinformatics (Oxford, England) · 2023Article
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5 authors.
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Abstract
Mathematical models of metabolic networks utilize simulation to study system-level mechanisms and functions. Various approaches have been used to model the steady state behavior of metabolic networks using genome-scale reconstructions, but formulating dynamic models from such reconstructions continues to be a key challenge. Here, we present the Mass Action Stoichiometric Simulation Python (MASSpy) package, an open-source computational framework for dynamic modeling of metabolism. MASSpy utilizes mass action kinetics and detailed chemical mechanisms to build dynamic models of complex biological processes. MASSpy adds dynamic modeling tools to the COnstraint-Based Reconstruction and Analysis Python (COBRApy) package to provide an unified framework for constraint-based and kinetic modeling of metabolic networks. MASSpy supports high-performance dynamic simulation through its implementation of libRoadRunner: the Systems Biology Markup Language (SBML) simulation engine. Three examples are provided to demonstrate how to use MASSpy: (1) a validation of the MASSpy modeling tool through dynamic simulation of detailed mechanisms of enzyme regulation; (2) a feature demonstration using a workflow for generating ensemble of kinetic models using Monte Carlo sampling to approximate missing numerical values of parameters and to quantify biological uncertainty, and (3) a case study in which MASSpy is utilized to overcome issues that arise when integrating experimental data with the computation of functional states of detailed biological mechanisms. MASSpy represents a powerful tool to address challenges that arise in dynamic modeling of metabolic networks, both at small and large scales.
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