The study investigates the global dynamical properties and stability of the cell-cycle regulatory network in budding yeast. Using a simplified dynamical model, the researchers demonstrate that the cell-cycle network is highly stable and robust. The G1 state, a biological stationary state, is a global attractor of the dynamics, and the cell-cycle sequence of protein states is a globally attracting trajectory. These properties are preserved even with small perturbations to the network. The results suggest that cellular regulatory networks are robustly designed for their functions. The study also compares the cell-cycle network with random networks, showing that the cell-cycle network has a super fixed point and a converging pathway, which are not typical in random networks. Additionally, the network is robust against various perturbations, maintaining its stability and the biological pathway. The findings highlight the robustness of the yeast cell-cycle network and its potential as a model for understanding the robustness of regulatory networks in general.The study investigates the global dynamical properties and stability of the cell-cycle regulatory network in budding yeast. Using a simplified dynamical model, the researchers demonstrate that the cell-cycle network is highly stable and robust. The G1 state, a biological stationary state, is a global attractor of the dynamics, and the cell-cycle sequence of protein states is a globally attracting trajectory. These properties are preserved even with small perturbations to the network. The results suggest that cellular regulatory networks are robustly designed for their functions. The study also compares the cell-cycle network with random networks, showing that the cell-cycle network has a super fixed point and a converging pathway, which are not typical in random networks. Additionally, the network is robust against various perturbations, maintaining its stability and the biological pathway. The findings highlight the robustness of the yeast cell-cycle network and its potential as a model for understanding the robustness of regulatory networks in general.