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BSTModelKit.jl: A Julia Package for Constructing, Solving, and Analyzing Biochemical Systems Theory Models.

Sandra Vadhin1, Jeffrey D Varner1

  • 1Robert Frederick Smith School of Chemical and Biomolecular Engineering Cornell University, Ithaca, NY 14853, USA.

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|March 30, 2026
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Summary

BSTModelKit.jl is an open-source Julia package for building and analyzing Biochemical Systems Theory (BST) models. It offers tools for S-system representations, simulations, and sensitivity analysis of biochemical networks.

Keywords:
JuliaS-systembiochemical systems theorymetabolic modelingpower-law formalismsystems biology

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Area of Science:

  • Biochemistry
  • Computational Biology
  • Systems Biology

Background:

  • Biochemical networks are complex systems requiring robust modeling tools.
  • Biochemical Systems Theory (BST) offers a power-law formalism for representing these networks.
  • Existing tools may lack flexibility or integration with modern computational environments.

Purpose of the Study:

  • Introduce BSTModelKit.jl, an open-source Julia package for BST model construction, simulation, and analysis.
  • Provide a user-friendly interface for defining and analyzing S-system models.
  • Facilitate efficient and flexible analysis of biochemical networks.

Main Methods:

  • Implementation of S-system representations within the Julia programming language.
  • Dynamic simulation using ordinary differential equation (ODE) integration via the SciML suite.
  • Steady-state computation and global sensitivity analysis (Morris and Sobol methods).

Main Results:

  • BSTModelKit.jl enables declarative model specification.
  • The package integrates with Julia's scientific computing ecosystem for efficient computation.
  • Demonstrated package capabilities through illustrative examples.

Conclusions:

  • BSTModelKit.jl provides a comprehensive and efficient toolkit for Biochemical Systems Theory modeling.
  • The package enhances the analysis of metabolic and regulatory networks.
  • It serves as a valuable resource for researchers in computational and systems biology.