Klipp Edda
Max Planck Institute for Molecular Genetics, Computational Systems Biology, Ihnestrasse 63-73, 14195 Berlin, Germany.
Yeast. 2007 Nov;24(11):943-59. doi: 10.1002/yea.1544.
Yeast molecular and cell biology has accumulated large amounts of qualitative and quantitative data of diverse cellular processes. The results are often summarized as verbal or graphical descriptions. Moreover, a series of mathematical models has been developed that should help to interpret such data, to integrate them into a coherent picture and to allow for an understanding of the underlying processes. Dynamic modelling of regulatory processes in yeast focuses on central carbon metabolism, on a number of selected signalling pathways and on cell cycle regulation. These models can explain questions of general relevance, such as whether the dynamics of a network can be understood from the combination of in vitro kinetics of its individual reactions. They help to elucidate complicated dynamic features, such as glycolytic oscillations, effects of feedback regulation or the optimal regulation of gene expression. The availability of comprehensive qualitative information, such as protein interactions or pathway composition, and sets of quantitative data make yeast a perfect model organism. Therefore, yeast-related data are often used to develop and examine computational approaches and modelling methods.
酵母分子与细胞生物学积累了大量关于各种细胞过程的定性和定量数据。这些结果通常被总结为文字或图形描述。此外,已经开发了一系列数学模型,这些模型有助于解释此类数据,将它们整合为一个连贯的图景,并让人理解潜在的过程。酵母中调控过程的动态建模聚焦于中心碳代谢、一些选定的信号通路以及细胞周期调控。这些模型可以解释具有普遍相关性的问题,比如一个网络的动态是否可以从其各个反应的体外动力学组合来理解。它们有助于阐明复杂的动态特征,如糖酵解振荡、反馈调节的作用或基因表达的最优调控。全面的定性信息(如蛋白质相互作用或通路组成)以及定量数据集的可得性使酵母成为完美的模式生物。因此,与酵母相关的数据常被用于开发和检验计算方法及建模方法。