Set-base dynamical parameter estimation and model invalidation for biochemical reaction networks |
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| Authors: | Philipp Rumschinski Steffen Borchers Sandro Bosio Robert Weismantel Rolf Findeisen |
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| Affiliation: | 1.Institute for Automation Engineering, Otto-von-Guericke-Universitis?t Magdeburg,Magdeburg,Germany;2.Institute for Mathematical Optimization, Otto-von-Guericke-Universit?t Magdeburg,Magdeburg,Germany;3.Magdeburg Centre for Systems Biology (MaCS), Otto-von-Guericke-Universit?t Magdeburg,Magdeburg,Germany;4.International Max Planck Research School (IMPRS), Max Planck Institute for Dynamics of Complex Technical Systems,Magdeburg,Germany |
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| Abstract: | Background Mathematical modeling and analysis have become, for the study of biological and cellular processes, an important complement to experimental research. However, the structural and quantitative knowledge available for such processes is frequently limited, and measurements are often subject to inherent and possibly large uncertainties. This results in competing model hypotheses, whose kinetic parameters may not be experimentally determinable. Discriminating among these alternatives and estimating their kinetic parameters is crucial to improve the understanding of the considered process, and to benefit from the analytical tools at hand. |
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