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

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 reduction is demonstrated on the example of kinetic model of yeast glycolysis. In parallel to the estimation of remaining range of optimisation potential the full search of combinations was combined with forward selection that allows reaching 91.4% of potential after optimising 625 parameter combinations. This result was reached by involving just seven out of fifteen adjustable parameters.