Pulse perturbations experimental test

Experimental Test of the Pulse Perturbation Method for Determining Causal Connectivities of Chemical Species in a Reaction Network... 

For an experimental test of the pulse perturbation method [1] we choose a part of glycolysis shown in fig. 6.1. There are similarities and some differences between the model in fig. 5.12 and the reaction system in fig. 6.1. The reaction system has reactants, enzymes, and some effectors. One point of interest in choosing this system is the test of detecting and identifying the split of the reaction chain, from glucose to F1,6BP, at the aldolase reaction into two chains, one terminating at G3P and the other at 3PG. 

Most of the methods outlined above are suitable for obtaining information on oscillatory reaction networks. As pointed out in several other chapters in this book, related methods can be used for determination of causal connectivities of species and deduction of mechanims in general nonoscillatory networks. Pulses of species concentration by an arbitrary amount have been proposed (see chapter 5) and experimentally applied to glycolysis (see chapter 6). Random perturbation by a species can be used and the response evaluated by means of correlation functions (see chapter 7) this correlation metric construction method has also been tested (see chapter 8). Another approach to determining reaction mechanisms by finding Jacobian matrix elements is described in Mihaliuk et al. [69]. 

In the interpretation and analysis of chromatographic data it is assumed that the system is linear. Kinetic and equilibrium parameters are determined by matching the experimental response curve to the dimensionless theoretical curve calculated from a suitable dynamic model for the system. The assumption of linearity is a valid approximation provided that the concentration change over which the response is measured is sufficiently small. In the linear regime the normalized response is independent of the magnitude of the perturbation, and variation of the pulse (or step) size therefore provides a simple and direct test of system linearity. 

---