AMICI: high-performance sensitivity analysis for large ordinary differential equation models

A Summary: Ordinary differential equation models facilitate the understanding of cellular signal transduction and other biological processes. However, for large and comprehensive models, the computational cost of simulating or calibrating can be limiting. AMICI is a modular toolbox implemented in C++/Python/MATLAB that provides efficient simulation and sensitivity analysis routines tailored for scalable, gradient-based parameter estimation and uncertainty quantification.

Automated summary

Ordinary differential equation models are useful for understanding biological processes like cellular signal transduction, but computational costs can be limiting for large models. AMICI is a modular toolbox implemented in multiple languages that provides efficient simulation and sensitivity analysis routines tailored for scalable, gradient-based parameter estimation and uncertainty quantification.