Control of Multistability through Local Sensitivity Analysis: Application to Cellular Decision-making Networks

Abstract

Control of multistable dynamical system has important applications, from physics to biology. Here, we attack this problem from the perspective of local sensitivity analysis. We develop sensitivity rules to control properties of continuous-time multistable dynamics with simple attractors, namely, the relative size and depth of their basins of attraction. Our parameter control signal is computationally cheap and provides counter-intuitive information about the sensitive parameters to be manipulated in an experimental setting.