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Piecewise affine approximations of fluxes and enzyme kinetics from in vivo 13 C labeling experiments
Author(s) -
Abate Alessandro,
Hillen Robert C.,
Aljoscha Wahl S.
Publication year - 2012
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.2798
Subject(s) - piecewise , scalability , affine transformation , biological system , kinetic energy , flux (metallurgy) , computer science , in silico , mathematics , kinetics , algorithm , chemistry , physics , mathematical analysis , pure mathematics , biochemistry , organic chemistry , quantum mechanics , database , gene , biology
SUMMARY Owing to the ever increasing amount of available information on metabolic networks and, in particular, to the increase in information content from in vivo 13 C dynamic labeling experiments, this work investigates the problem of reconstructing dynamic fluxes and enzyme kinetics. The model structure is based on the use of piecewise affine approximations. The optimization procedure at the basis of the model identification is improved by separating the parameter estimation procedure into two different phases. As a first step, a dynamic flux profile in time is reconstructed using functions that are piecewise affine (in time). To achieve scalability for this step, several approaches have been developed and compared. Afterwards, the time‐dependent profiles are embedded in the concentration space and the enzyme kinetic functions for single reactions are identified independently. This is an advantage compared with standard complete kinetic network approaches, which are typically characterized by hundreds of parameters, because now only a few need to be optimized simultaneously. Additionally, different kinetic formats can be rapidly compared. The overall approach is demonstrated using an informative in silico experiment. Copyright © 2012 John Wiley & Sons, Ltd.