SensSB: a software toolbox for the development and sensitivity analysis of systems biology models. SensSB (Sensitivity Analysis for Systems Biology) is an easy to use, MATLAB-based software toolbox, which integrates several local and global sensitivity methods that can be applied to a wide variety of biological models. In addition to addressing the sensitivity analysis problem, SensSB aims to cover all the steps involved during the modeling process. The main features of SensSB are: (i) derivative and variance-based global sensitivity analysis, (ii) pseudo-global identifiability analysis, (iii) optimal experimental design (OED) based on global sensitivities, (iv) robust parameter estimation, (v) local sensitivity and identifiability analysis, (vi) confidence intervals of the estimated parameters and (vii) OED based on the Fisher Information Matrix (FIM). SensSB is also able to import models in the Systems Biology Mark-up Language (SBML) format. Several examples from simple analytical functions to more complex biological pathways have been implemented and can be downloaded together with the toolbox. The importance of using sensitivity analysis techniques for identifying unessential parameters and designing new experiments is quantified by increased identifiability metrics of the models and decreased confidence intervals of the estimated parameters.
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References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
- Weilong Hu; Yannis Pantazis; Markos Katsoulakis: ISAP-MATLAB Package for Sensitivity Analysis of High-Dimensional Stochastic Chemical Networks (2018) not zbMATH
- Bobak, C.; Kunze, H.: Modelling an aquaponic ecosystem using ordinary differential equations (2016)
- Khoshnaw, Sarbaz H. A.: Reduction of a kinetic model of active export of importins (2015)
- Rodriguez-Fernandez, Maria; Banga, Julio R.; Doyle, Francis J. III: Novel global sensitivity analysis methodology accounting for the crucial role of the distribution of input parameters: application to systems biology models (2012)