Department of Mathematics, University of Nebraska at Omaha, Omaha, Nebraska, United States of America.
PLoS One. 2012;7(10):e45780. doi: 10.1371/journal.pone.0045780. Epub 2012 Oct 1.
It has been suggested that irreducible sets of states in Probabilistic Boolean Networks correspond to cellular phenotype. In this study, we identify such sets of states for each phase of the budding yeast cell cycle. We find that these "ergodic sets" underly the cyclin activity levels during each phase of the cell cycle. Our results compare to the observations made in several laboratory experiments as well as the results of differential equation models. Dynamical studies of this model: (i) indicate that under stochastic external signals the continuous oscillating waves of cyclin activity and the opposing waves of CKIs emerge from the logic of a Boolean-based regulatory network without the need for specific biochemical/kinetic parameters; (ii) suggest that the yeast cell cycle network is robust to the varying behavior of cell size (e.g., cell division under nitrogen deprived conditions); (iii) suggest the irreversibility of the Start signal is a function of logic of the G1 regulon, and changing the structure of the regulatory network can render start reversible.
有人认为，概率布尔网络中的不可约状态集对应于细胞表型。在这项研究中，我们确定了芽殖酵母细胞周期每个阶段的这样的状态集。我们发现，这些“遍历集”是细胞周期每个阶段细胞周期蛋白活性水平的基础。我们的结果与几个实验室实验的观察结果以及微分方程模型的结果相比较。对该模型的动力学研究：（i）表明，在随机外部信号下，细胞周期蛋白活性的连续振荡波和 CKIs 的相反波从基于布尔的调控网络的逻辑中出现，而不需要特定的生化/动力学参数；（ii）表明，酵母细胞周期网络对细胞大小的变化行为具有鲁棒性（例如，氮饥饿条件下的细胞分裂）；（iii）表明起始信号的不可逆性是 G1 调控子逻辑的一个功能，并且改变调控网络的结构可以使起始变得可逆。
