Editorial for special issue on 'Robustness in systems biology: methods and applications'

Robustness is a key feature of biological systems and intrinsically a system characteristic as it allows to upkeep essential properties such as survival despite various internal or external perturbations, unpredictable environments, stochastic events and unreliable components, etc. Analysing robustness of such systems is however not simple, due to their inherent nonlinearity and complex nature. This special issue aims to present novel results in the development of robustness analysis and design methodologies driven by the need of understanding biological systems.

Modelling is essential for understanding complex, dynamical systems. Model analysis is important both during the modelling process to highlight the most important parts and elucidate possible shortcomings and afterwards to uncover fragile parts possibly suited for drug design. Feedback control plays a fundamental role in achieving robustness and it is prevalent in biological systems from the molecular and cellular levels to the organism level. Therefore, system theoretical methodologies are ideally suited to analyse the robustness of biological systems. There are a number of recent examples showing how control and system methods can be used as a tool for bringing new insights in to biological systems. These systems, however, have peculiar properties that might require the development of novel, specially tailored analysis tools.

This special focus section presents four papers, with a scope from modelling over analysis to experiment design. The first two papers use a modified version of the structured singular value approach for uncovering fragile parts in signalling models. J-S. Kim et al. analyse the cAMP oscillations in aggregating Dictyostelium cells, using this to guide the modelling process towards a more robust model. C. Trané and E. Jacobsen perturb statically and dynamically two signalling models, with a particular focus on bifurcation point. They apply their analyses to the glycolytic oscillation as well as to a bistable MAPK pathway.