Comparison of approaches for parameter identifiability analysis of biological systems | Zendy

Andreas Raue | Zendy; Johan Karlsson | Zendy; Maria Pia Saccomani | Zendy; Mats Jirstrand | Zendy; Jens Timmer | Zendy

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Comparison of approaches for parameter identifiability analysis of biological systems

Author(s) -

Andreas Raue,

Johan Karlsson,

Maria Pia Saccomani,

Mats Jirstrand,

Jens Timmer

Publication year - 2014

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btu006

Subject(s) - identifiability , computer science , ordinary differential equation , a priori and a posteriori , benchmark (surveying) , matlab , strengths and weaknesses , experimental data , pairwise comparison , theoretical computer science , differential equation , data mining , algorithm , mathematics , machine learning , artificial intelligence , programming language , statistics , philosophy , geodesy , epistemology , geography , mathematical analysis

Modeling of dynamical systems using ordinary differential equations is a popular approach in the field of Systems Biology. The amount of experimental data that are used to build and calibrate these models is often limited. In this setting, the model parameters may not be uniquely determinable. Structural or a priori identifiability is a property of the system equations that indicates whether, in principle, the unknown model parameters can be determined from the available data.

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