Predicting Synchronization of an Electronic Genetic Network

Abstract

Multiple shooting method has been applied to the parameter estimation of phase equations for experimental data. Application to electronic genetic network has shown that the present approach is good enough to predict the regime of synchronization from a single measurement data. Advantage of this approach is that it can be applied to network systems and that all parameters are estimated simultaneously. Moreover, extension is possible to the case of nonuniform coupling C_<i,j> as well as inhomogeneous interaction function H_i(&lrtri;θ). It is important to note that the estimation results depend crucially upon (I) coupling strength C set for the measurement data and (II) network size. At least, C should be taken from non-synchronous regime. The detailed results will be reported elsewhere. A big future challenge is to apply the present approach to a network of real suprachiasmatic nucleus (SCN) neurons.