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• W6052796 abstract "Biological models are often modelled by nonlinear ordinary differential equations involving unknown parameters such as reaction rates. The unknown parameters of these models need to be estimated from input–output data often collected in delicate experiments. One goal of this chapter is to make researchers in system biology aware of the relevance of testing structural identifiability of the dynamic model under study before applying numerical algorithms for parameter estimation.A parameter identifiability method based on differential algebra is presented and discussed. This method can be applied to systems described by differential equations involving polynomial or rational nonlinearities. It has been implemented in the software tool DAISY, which can check structural global identifiability of nonlinear systems in a fully automatic way. It is also shown how one can successfully check identifiability of some nonpolynomials (e.g., exponential nonlinearities). The role of initial conditions in identifiability analysis is also discussed." @default.
• W6052796 created "2016-06-24" @default.
• W6052796 creator A5027434678 @default.
• W6052796 date "2014-01-01" @default.
• W6052796 modified "2023-09-23" @default.
• W6052796 title "Structural Identifiability of Biological and Physiological Systems" @default.
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• W6052796 doi "https://doi.org/10.1016/b978-0-12-411557-6.00004-5" @default.
• W6052796 hasPublicationYear "2014" @default.
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