Mathematical Modeling - Biochemical Networks in Yeast

描述（由申请人提供）：该项目的目标是开发数学工具，根据实验数据对生化网络进行建模。 然后，这些工具将被应用到转录组学，蛋白质组学和代谢组学数据收集从网络的10个基因的模式生物酿酒酵母，参与氧化应激反应。 建议的方法是开发一个两阶段的建模过程。将生化网络视为一个连续的动力系统，由一组常微分方程描述，我们首先使用数值方法通过离散时间系统近似该系统。然后使用几种工具来分析这个离散系统。这些工具之一是进一步减少，通过将变量的状态值分类到有限的状态集合中来实现。由此产生的框架允许使用发达的方法，从计算代数研究整个空间的可能模型的离散时间系统的有限状态集。 为了证明和测试的数学方法，实验将进行了面包酵母酿酒酵母。通过添加氢过氧化枯烯和氧化应激干扰野生型酵母的细胞培养物，并在一定时间内测量样品。实验将重复十次，每次使用不同的基因缺失突变体。将根据数学模型产生的假设选择突变体。除了支持数学发展外，这些实验还有望揭示谷胱甘肽代谢和相关抗氧化分子（如L-抗坏血酸）调节的细节。

DESCRIPTION (provided by applicant): The goal of this project is to develop mathematical tools to model biochemical networks from experimental data. These tools will then be applied to transcriptomics, proteomics, and metabolomics data collected from a network of ten genes of the model organism Saccharomyces cerevisiae that are involved in oxidative stress response. The proposed approach is to develop a two-stage modeling process. Viewing a biochemical network as a continuous dynamical system, described by a collection of ordinary differential equations, we first approximate the system by a discrete-time system, using numerical methods. Several tools are then used to analyze this discrete system. One of these tools is a further reduction, achieved by categorizing the state values of the variables into a finite set of states. The resulting framework allows the use of well-developed methods from computational algebra to study the whole space of possible models for the discrete-time system on a finite state set. To demonstrate and test the mathematical methodologies, experiments will be carded out with the baker's yeast Saccharomyces cerevisiae. Cell cultures of wild type yeast will be perturbed by addition of cumene hydroperoxide, and oxidative stress, and samples will be measured in a time course. The experiment will be repeated ten times, each time with a different gene deletion mutant. Mutants will be selected according to the hypotheses generated by the mathematical models. In addition to supporting the mathematical developments, the experiments are expected to reveal details about the regulation of glutathione metabolism and related antioxidant molecules (such as Lascorbic acid).