Hybrid discrete algorithm for the modelling of gene regulatory networks

Abstract

Mathematical modelling and simulation can aid the analysis and design of gene regulatory networks (GRNs). GRN modelling approaches can be divided into two major categories, deterministic and stochastic. In this paper we present a new algorithm for GRN modelling called hybrid discrete algorithm (HDA). It introduces stochastic effects into an underlying deterministic approach and is based on implicit rules that make modular, bottom-up modelling possible, without having to derive specific network equations. The algorithm explicitly models competitive binding of activators and repressors to the same binding site. Furthermore, it takes into account a limited number of binding site repeats. We demonstrate and validate the algorithm on the repressilator model.