Developing a Highly Efficient Numerical ODE Solver in the Systems Biology Simulation Core Library

The field of computational biology depends significantly on mathematical modeling to simulate complex biological simulations, often involving solution of large systems of ordinary differential equations, which describe dynamic biological processes. Accurate and efficient numerical solvers are essential for these simulations to predict correct behaviour. LSODA (Livermore Solver for Ordinary Differential equations Automatic) is a well-established ODE solver known for its ability to dynamically switch between stiff and nonstiff methods, making it particularly suitable for biological models where stiffness can vary over time. However, LSODA’s widely used implementations are primarily in C/C++ and Fortran, creating a barrier for researchers working in Java-based environments. This project aims to bridge that gap by implementing a robust, optimized, thoroughly tested, and fully functional Java-based version of the LSODA algorithm within SBSCL (Systems Biology Simulation Core Library).