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Dynamic models of biochemical networks usually are described as a system of nonlinear differential equations. In case of optimization of models for purpose of parameter estimation or design of new properties mainly numerical methods are used. That causes problems of optimization predictability as most of numerical optimization methods have stochastic(More)
The search for minimal set of adjustable parameters through optimising a kinetic model of biochemical networks is needed in industrial biotechnology to increase the productivity of industrial organism strains while keeping low the chance of causing unwanted side effects of implemented changes. As the search for minimal set of adjustable parameters is of(More)
Selecting an efficient small set of adjustable parameters to improve metabolic features of an organism is important for a reduction of implementation costs and risks of unpredicted side effects. In practice, to avoid the analysis of a huge combinatorial space for the possible sets of adjustable parameters, experience-, and intuition-based subsets of(More)
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