The lecture aims at giving new results on the structural sensitivity of biological regulation networks represented by threshold Boolean networks and ruled by Hopfield-like evolution laws classically used in the context of neural and genetic networks. Indeed, the objective is to present how certain changes and/or perturbations in such networks can modify significantly their asymptotic behaviour. More precisely, we focus on three different kinds of what we think to be relevant in the biological area of robustness (in both theoretical and applied frameworks): the boundary - in graph sense - sensitivity (like hormonal activations), the state sensitivity (like microRNAs inhibitions) and the updating sensitivity (like block-sequential genetic expression).