酵母细胞周期脉冲发生器模型与多个振荡和检查点突变数据集一致
A yeast cell cycle pulse generator model shows consistency with multiple oscillatory and checkpoint mutant datasets
摘要：
驱动酵母细胞周期进展的调节机制似乎由转录因子（TF）、细胞周期蛋白依赖性激酶（CDK）和泛素连接酶的相互作用网络组成。从系统的角度来看，控制性调节网络必须在增殖阶段产生稳健的周期性行为，但在不利条件触发检查点停滞时有能力停止循环。网络的各个组成部分如何对这些动态表型做出贡献仍然是一个悬而未决的问题。在这里，我们评估了一个简化的网络模型的能力，假设包含细胞周期进程的调控的关键要素，重现观察到的转录组行为。我们匹配的时间序列数据从循环和检查点被捕的细胞的一个相对简单的细胞周期网络模型的预测，使用异步多级布尔方法。我们表明，这个单一的网络模型，尽管它的简单，是能够表现出类似的动态行为的数据集在大多数情况下，而它不，我们确定的假设，表明网络的缺失组件。
英文摘要：
The regulatory mechanisms driving progression of the yeast cell cycle appears to be comprised of an interacting network of transcription factors (TFs), cyclin-dependent kinases (CDK) and ubiquitin ligases. From a systems perspective the controlling regulatory network must produce robust periodic behavior during proliferative phases, but have the capability to halt the cycle when unfavorable conditions trigger a checkpoint arrest. How the individual components of the network contribute to these dynamical phenotypes remains an open question. Here we evaluate the capability of a simplified network model hypothesized to contain key elements of the regulation of cell-cycle progression to reproduce observed transcriptomic behaviors. We match time-series data from both cycling and checkpoint arrested cells to the predictions of a relatively simple cell-cycle network model using an asynchronous multi-level Boolean approach. We show that this single network model, despite its simplicity, is capable of exhibiting dynamical behavior similar to the datasets in most cases, and where it does not, we identified hypotheses that suggest missing components of the network.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
