Abstract
A dynamical system model is presented in this paper for genetic regulatory networks with hybrid regulatory mechanism. The sufficient conditions for the stability of the proposed model are established based on the Lyapunov functional method and linear matrix inequality techniques. To test the effectiveness and correctness of our theoretical results, illustrative examples regarding modified repressilator and modified 5-node genetic network models are also presented.
Highlights
Synthetic biology is an emerging field that aims to design and synthesize biological networks or devices that perform a desired function in a predictable manner
The study of genetic regulatory networks (GRNs) has received a major impetus from the recent development of experimental techniques allowing the measurement of patterns of gene expression in a massively parallel way [10], and becomes a fundamental challenge in synthetic biology as it explains the interactions between genes and proteins to form a complex system that performs complicated biological functions [7,35]
The organization of the paper is as follows: In Sect. 2, we present a model for GRNs with hybrid regulatory mechanism by introducing a parameter θ for measuring the relative contribution rate of direct regulatory
Summary
Synthetic biology is an emerging field that aims to design and synthesize biological networks or devices that perform a desired function in a predictable manner. In the absence of a time delay, a desired function, for example, toggle switch in [12], oscillation in [11] and stability in [3,8,19], can be generated by the ordinary differential equation (ODE) model. If an equilibrium of a neural network is globally, asymptotically stable, it means that the domain of attraction of the equilibrium point is the whole space, and convergence is in real time It is of both theoretical and practical importance to study the stability of GRNs. the gene regulation is an intrinsically noisy process; this is always subject to intracellular and extracellular noise perturbations, which are caused by the random births and deaths of individual molecules, along with extrinsic noise due to fluctuations in the environment. If not explicitly stated, matrices are assumed to have compatible dimensions. λmax(P) denotes the maximal eigenvalue of a square matrix P
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
