Intervention in biological phenomena represented by genetic regulatory networks: A variable structure approach

The utilization of mathematical tools in the analysis and synthesis of models representing biological phenomena is rapidly growing. Adding to these efforts, in this paper, a mathematical method based on the sliding mode control approach will be used for the purpose of developing a therapeutic intervention strategy for a class of biological phenomena. Such an intervention scheme aims at moving an undesirable state of a diseased network towards a more desirable state using drugs to act on some genes/metabolites that characterize the undesirable behavior. S-systems, which offer a good compromise between accuracy and mathematical flexibility, are a promising framework for modeling the dynamical behavior of biological phenomena as well as genetic regulatory networks. Since biological phenomena modeled by S-systems are complex nonlinear processes, the need for robust nonlinear intervention strategies that are capable of guiding the target variables to their desired values often arises. The main objective of this paper is to develop an intervention scheme based on sliding mode control theory, sometimes referred to as variable structure control theory, and evaluate the robustness of the sliding mode intervention scheme in the presence of model parameter uncertainties. The proposed intervention strategy is applied to a glycolytic-glycogenolytic pathway model and the simulation results demonstrate the effectiveness of the proposed scheme.