Back to Search Start Over

GenSSI 2.0: multi-experiment structural identifiability analysis of SBML models

Authors :
European Commission
German Research Foundation
Ligon, Thomas S.
Fröhlich, Fabian
Chis, O.
Banga, Julio R.
Balsa-Canto, Eva
Hasenauer, Jan
European Commission
German Research Foundation
Ligon, Thomas S.
Fröhlich, Fabian
Chis, O.
Banga, Julio R.
Balsa-Canto, Eva
Hasenauer, Jan
Publication Year :
2018

Abstract

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.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1103436446
Document Type :
Electronic Resource