• Corpus ID: 4517674

Reduction of Combinatorial Space of Adjustable Kinetic Parameters of Biochemical Network Models in Optimisation Task

@inproceedings{Mozga2014ReductionOC,
  title={Reduction of Combinatorial Space of Adjustable Kinetic Parameters of Biochemical Network Models in Optimisation Task},
  author={Ivars Mozga and Egils Stalidzans},
  year={2014}
}
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 combinatorial nature, the search space becomes very large even at relatively small number of parameters. The presented approach of search space… 

Figures from this paper

Model-based metabolism design: constraints for kinetic and stoichiometric models

TLDR
The limitations of applicability of particular constraints for kinetic and stoichiometric models are addressed and several new approaches of cellular analysis have made possible the application of constraints like cell size, surface, and resource balance.

References

SHOWING 1-10 OF 22 REFERENCES

Two stage optimization of biochemical pathways using parallel runs of global stochastic optimization methods

A disadvantage of global stochastic optimization methods is the stochastic convergence of the best value of the objective function to the global optimum. In spite those methods are widely used

A Computational Procedure for Optimal Engineering Interventions Using Kinetic Models of Metabolism

TLDR
A general computational procedure to determine which genes/enzymes should be eliminated, repressed or overexpressed to maximize the flux through a product of interest for general kinetic models is proposed.

Non-linear optimization of biochemical pathways: applications to metabolic engineering and parameter estimation

TLDR
A generic approach to combine numerical optimization methods with biochemical kinetic simulations is described, suitable for use in the rational design of improved metabolic pathways with industrial significance and for solving the inverse problem of metabolic pathways.

Convergence dynamics of biochemical models to the global optimum

TLDR
The properties of convergence dynamics of evolutionary programming and particle swarm are studied optimizing yeast glycolysis by COPASI software adjusting parameters of one, five, ten and fifteen reactions with five identical runs for each case.

Computer-Aided Design of Metabolic Networks

TLDR
This contribution presents results obtained from a model based design of metabolic networks, using topological analysis for exploring the metabolic architecture and a strategy for the optimization of product formation rates is presented by means of the ethanol formation rate in Saccharomyces cerevisiae.

ConvAn: A convergence analyzing tool for optimization of biochemical networks

Towards a genome-scale kinetic model of cellular metabolism

TLDR
A method for building a parameterized genome-scale kinetic model of a metabolic network and, whilst approximative, has considerably broader remit than any existing models of its type.

Full-scale model of glycolysis in Saccharomyces cerevisiae.

In silico strategy to rationally engineer metabolite production: A case study for threonine in Escherichia coli

TLDR
Improvement of threonine production via pyruvate kinase deletion in Escherichia coli is used as a case study to demonstrate a partial application of the Universal Method, which includes performing sensitivity analysis.