| Literature DB >> 33821950 |
Fabian Fröhlich1, Daniel Weindl2, Yannik Schälte2,3, Dilan Pathirana4, Łukasz Paszkowski5, Glenn Terje Lines5, Paul Stapor2,3, Jan Hasenauer2,3,4.
Abstract
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. AVAILABILITY: 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. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.Year: 2021 PMID: 33821950 DOI: 10.1093/bioinformatics/btab227
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937