Exploring Design Principles of Gene Regulatory Networks via Pareto Optimality

One central problem in systems and synthetic biology is to characterize the biological functions of regulatory network motifs. Here we consider recent model-based exploration approaches used to identify motifs capable of performing a specific biological task. In this work, we propose an optimization based strategy where the motivation is twofold: on the one hand, to introduce efficiency and optimality in the search, by using global mixed integer nonlinear optimization methods. On the other hand, to incorporate multiple design objectives (Pareto optimality), in order to cope with realistic trade-offs observed in nature. The potential of this approach is illustrated through an example where we explore the design principles underlying stripe-forming motifs. (C) 2016, IFAC (International Federation of Antomatic Control) Hosting by Elsevier Ltd. All rights reserved.