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GenSSI 2.0: Multi-experiment structural identifiability analysis of SBML models.
Bioinformatics 34, 1421-1423 (2017)
Publ. Version/Full Text
Research data
DOI
PMC
Motivation Mathematical modeling using ordinary differential equations is used in systems biology to improve the understanding of dynamic biological processes. The parameters of ordinary differential equation models are usually estimated from experimental data. To analyze a priori the uniqueness of the solution of the estimation problem, structural identifiability analysis methods have been developed. Results We introduce GenSSI 2.0, an advancement of the software toolbox GenSSI (Generating Series for testing Structural Identifiability). GenSSI 2.0 is the first toolbox for structural identifiability analysis to implement Systems Biology Markup Language import, state/parameter transformations and multi-experiment structural identifiability analysis. In addition, GenSSI 2.0 supports a range of MATLAB versions and is computationally more efficient than its previous version, enabling the analysis of more complex models.
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Publication type
Article: Journal article
Document type
Scientific Article
ISSN (print) / ISBN
1367-4803
e-ISSN
1367-4811
Journal
Bioinformatics
Quellenangaben
Volume: 34,
Issue: 8,
Pages: 1421-1423
Publisher
Oxford University Press
Publishing Place
Oxford
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Institute of Computational Biology (ICB)