TYPE-DEPENDENT STOCHASTIC ISING MODEL DESCRIBING THE DYNAMICS OF A NON-SYMMETRIC FEEDBACK MODULE

We study an alternative approach to model the dynamical behaviors of biological feedback loop, that is, a type-dependent spin system, this class of stochastic models was introduced by Fernandez et. al {[}13], and are useful since take account to inherent variability of gene expression. We analyze a non symmetric feedback module being an extension for the repressilator, the first synthetic biological oscillator, invented by Elowitz and Leibler {[}7]. We consider a mean-field dynamics for a type-dependent Ising model, and then study the empirical-magnetization vector representing concentration of molecules. We apply a convergence result from stochastic jump processes to deterministic trajectories and present a bifurcation analysis for the associated dynamical system. We show that non-symmetric module under study can exhibit very rich behaviours, including the empirical oscillations described by repressilator. (AU)