biostudies-literatureFrohlich FGerman Research FoundationGermany's Excellence StrategyHuman Frontier Science ProgramGermany’s Excellence StrategyNational Institute of HealthNCI NIH HHSFederal Ministry of Economic Affairs and EnergyFederal Ministry of Education and Research of GermanyEuropean Union's Horizon 2020 research and innovation programEuropean Union’s Horizon 2020 research and innovation program3676-3677https://www.ebi.ac.uk/biostudies/studies/S-EPMC8545331biostudies-literatureUnknown37(20)<h4>Summary</h4>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.<h4>Availabilityand implementation</h4>AMICI is published under the permissive BSD-3-Clause license with source code publicly available on https://github.com/AMICI-dev/AMICI. Citeable releases are archived on Zenodo.<h4>Supplementary information</h4>Supplementary data are available at Bioinformatics online.Bioinformatics (Oxford, England)AMICI: high-performance sensitivity analysis for large ordinary differential equation models.PMC8545331EXC-2047/1–39068581301ZX1705A01ZX1916A16KN074236U54-CA225088LT000259/2019-L1U54 CA225088HA7376/1-1EXC-2047/1-390685813686282031L0159CHasenauer JPathirana DFrohlich FSchalte YWeindl DStapor PPaszkowski LLines GTfalseAMICI: high-performance sensitivity analysis for large ordinary differential equation models.<h4>Summary</h4>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.<h4>Availabilityand implementation</h4>AMICI is published under the permissive BSD-3-Clause license with source code publicly available on https://github.com/AMICI-dev/AMICI. Citeable releases are archived on Zenodo.<h4>Supplementary information</h4>Supplementary data are available at Bioinformatics online.2021-01-01T00:00:00Z2021 Oct2025-04-26T16:53:05.639Z2025-04-06T15:21:20.476ZS-EPMC85453313382195010.1093/bioinformatics/btab227