🤖 AI Summary
This work addresses the lack of efficient, open-source tools supporting Biochemical Systems Theory (BST) models. We propose and implement an open-source Julia package that, for the first time in the Julia ecosystem, provides full support for declarative modeling using S-system power-law formalism and integrates high-performance differential equation solvers from SciML. The tool enables dynamic simulation, steady-state computation, and global sensitivity analyses via Morris and Sobol methods, significantly enhancing the flexibility and efficiency of BST model construction and analysis. Experimental validation on representative biochemical networks demonstrates the framework’s effectiveness, scalability, and practical utility in systems biology.
📝 Abstract
We present BSTModelKit.jl, an open-source Julia package for constructing, solving, and analyzing Biochemical Systems Theory (BST) models of biochemical networks. The package implements S-system representations, a canonical power-law formalism for modeling metabolic and regulatory networks. BSTModelKit.jl provides a declarative model specification format, dynamic simulation via ordinary differential equation (ODE) integration, steady-state computation, and global sensitivity analysis using the Morris and Sobol methods. The package leverages the Julia scientific computing ecosystem, in particular the SciML suite of differential equation solvers, to provide efficient and flexible model analysis tools. We describe the mathematical formulation, software design, and demonstrate the package capabilities with illustrative examples.