07. Giulia Giordano: Practical resilience of biological systems

Full title. Practical resilience of biological systems: facing stochastic perturbations for robust control design
Abstract. Biological systems have evolved to maintain properties that are crucial for survival. Robustness and resilience are associated with a system's ability to preserve its functions despite uncertainties, fluctuations and perturbations, both intrinsic and extrinsic. Examples range from cells sustaining stable protein production, to organisms maintaining homeostasis, to colonies that repeat consistent density patterns over time.
However, due to the multidisciplinary nature of the research topic, numerous competing definitions of robustness and, more so, of resilience coexist and often lack a rigorous control-theoretic formulation. To bridge this gap, and foster mathematical analysis and applications in a broad set of natural systems, in [1] we consider a family of ODE systems consisting of stochastic perturbations of a nominal deterministic system, and we introduce formal definitions of resilience of such a family of systems aimed at probabilistically quantifying its ability to preserve a prescribed attractor.
We show that our proposed definitions generalise the notion of probabilistic robustness, and we demonstrate their efficacy when applied to widely used models in biology: a Levin-Segel population model with diffusion, giving rise to the formation of Turing patterns, and a gene regulatory network. Our definitions can be applied to gain insight into the behaviour of biological systems and to derive indicators to assess resilience from empirical observations. They can also be easily extended to networks and additional cases of uncertainties and disturbances, to encompass a wider framework.
Bio. Giulia Giordano is a Full Professor at the Department of Industrial Engineering, University of Trento, Italy, where she leads the Dynamical Networks and Systems Biology group. She received the B.Sc. and M.Sc. degrees summa cum laude, and the Ph.D. degree with honours in Systems and Control Theory, from the University of Udine, Italy. She was a Research Fellow at Lund University, Sweden, from 2016 to 2017, and an Assistant Professor at the Delft University of Technology, The Netherlands, from 2017 to 2019. Giulia serves as an Associate Editor for the IEEE Control Systems Letters and for Automatica. She was selected as Outstanding Reviewer by the IEEE Transactions on Automatic Control in 2016 and by the Annals of Internal Medicine in 2020, and as the Outstanding Associate Editor of the IEEE Control Systems Letters in 2021. Giulia received the EECI Ph.D. Award 2016, the NAHS Best Paper Prize 2017, and the SIAM Activity Group on Control and Systems Theory Prize 2021 for "significant contributions to the development of innovative methodologies for the structural analysis of networked control systems and their applications to biological networks". Her main research interests include the analysis and the control of dynamical networks, with applications especially to biology and epidemiology.