Benchmarking of numerical integration methods for ODE models of biological systems.

ABSTRACT: Ordinary differential equation (ODE) models are a key tool to understand complex mechanisms in systems biology. These models are studied using various approaches, including stability and bifurcation analysis, but most frequently by numerical simulations. The number of required simulations is often large, e.g., when unknown parameters need to be inferred. This renders efficient and reliable numerical integration methods essential. However, these methods depend on various hyperparameters, which strongly impact the ODE solution. Despite this, and although hundreds of published ODE models are freely available in public databases, a thorough study that quantifies the impact of hyperparameters on the ODE solver in terms of accuracy and computation time is still missing. In this manuscript, we in

SUBMITTER: Stadter P 

PROVIDER: S-EPMC7846608 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature