Stochastic sensitivity and variability of glycolytic oscillations in the randomly forced Sel’kov model

In present paper, we study underlying mechanisms of the stochastic excitability in glycolysis on the example of the model proposed by Sel’kov. A stochastic variant of this model with the randomly forced influx of the substrate is considered. Our analysis is based on the stochastic sensitivity function technique. A detailed parametric analysis of the stochastic sensitivity of attractors is carried out. A range of parameters where the stochastic model is highly sensitive to noise is determined, and a supersensitive Canard cycle is found. Phenomena of the stochastic excitability and variability of forced equilibria and cycles are demonstrated and studied. It is shown that in the zone of Canard cycles noise-induced chaos is observed.