Approximate statistical dynamics of a genetic feedback circuit

摘要: Auto-regulation, a process wherein protein negatively regulates its own production, is common motif in gene expression networks. Negative feedback plays critical role buffering intracellular fluctuations concentrations around optimal value. Due to the nonlinearities present these feedbacks, moment dynamics are typically not closed, sense that time derivative of lower-order statistical moments copy number depends on high-order moments. Moment equations closed by expressing higher-order as nonlinear functions moments, technique commonly referred closure. Here, we compare performance different closure techniques. Our results show used method, which assumes priori population counts normally distributed, performs poorly. In contrast, conditional derivative-matching, novel scheme proposed here provides good approximation exact across parameter regimes. summary our study new method for studying stochastic genetic negative circuits, and can be extended probe noise more complex