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A Priori Parameter Identifiability in Complex Reaction Networks
Published in Elsevier B.V.
2018
Volume: 51
   
Issue: 15
Pages: 760 - 765
Abstract
A priori parameter identifiability is an important element in building reliable models for complex reaction networks in systems biology and chemical engineering. Differential algebra has been widely used to study a priori structural identifiability of nonlinear systems, and also implemented in several software tools, for example, DAISY (Differential Algebra for Identifiability of SYstems) (Bellu et al., Computer methods and programs in biomedicine, 88(1), 2017). This technique usually fails for complex reaction networks which involve several reactions and species. In this paper, we use the concept of extent of reaction to simplify the procedure for testing identifiability. A linear transformation is used to convert the system from the concentration domain to the extent domain so that the input output map is readily generated without use of Ritt's pseudo–division algorithm. Then, further identifiability can be studied. The proposed approach is illustrated using a complex reaction network. © 2018
About the journal
JournalData powered by TypesetIFAC-PapersOnLine
PublisherData powered by TypesetElsevier B.V.
ISSN24058963
Open AccessYes
Concepts (10)
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    Algebra
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    Differential equations
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    Linear transformations
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    Mathematical transformations
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    COMPLEX REACTIONS
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    DIVISION ALGORITHMS
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    EXTENT DOMAIN
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    PARAMETER IDENTIFIABILITY
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    Systems biology
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    Complex networks