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AMICI: High-performance sensitivity analysis for large ordinary differential equation models.
Bioinformatics 37, 3676-3677 (2021)
Publ. Version/Full Text
Research data
DOI
PMC
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.
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Publication type
Article: Journal article
Document type
Scientific Article
ISSN (print) / ISBN
1367-4803
Journal
Bioinformatics
Quellenangaben
Volume: 37,
Issue: 20,
Pages: 3676-3677
Publisher
Oxford University Press
Publishing Place
Oxford
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Institute of Computational Biology (ICB)
Grants
Federal Ministry of Economic Affairs and Energy
National Institute of Health
Human Frontier Science Program
German Research Foundation
Federal Ministry of Education and Research of Germany
European Union
National Institute of Health
Human Frontier Science Program
German Research Foundation
Federal Ministry of Education and Research of Germany
European Union