SGER: A new approach to the decomposition of complex chemical kinetics

SGER：复杂化学动力学分解的新方法

• 批准号: 0806266
• 负责人: Jianshu Cao
• 金额: $ 20万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-06-15 至 2011-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0806266&HistoricalAwards=false
• 关键词: SGER; new; approach; decomposition; complex

Jianshu Cao of the Massachusetts Institute of Technology is supported by a Small Grant for Exploratory Research from the Theoretical and Computational Chemistry program for research to develop a method to decompose complex chemical reactions into irreducible schemes that provide the generic structures for a class of reactions and are invariant to changes made to the sub-schemes. The concept of irreducible generic schemes is helpful in the analysis and classification of dynamic behavior and facilitates the interpretation of experimental measurements. The work consists of three stages. 1. A first-order kinetic network is decomposed by identifying two kinetic motifs, i.e., sequential chain reactions and branching reactions. Systematically concatenating chain reactions and side-branches, the investigators can then reduce a complex reaction to its generic form, each link of which represents a sub-scheme associated with a complex waiting time distribution function. When a kinetic step is altered within a sub-scheme, the waiting time distribution function changes accordingly, but the overall generic scheme and related dynamic quantities will remain the same functional forms. 2. A high-order kinetic network is then expanded around its steady state solution to the rate equation, which retains the full non-linearity in the dynamic behavior of average concentration. The correlations and fluctuations near the steady state are approximated by a linear form for the solution, an approach directly related to stability analysis methods for dynamic behavior and response measurements. In linearized networks, the feed-back or feed-forward mechanism defines a third motif, which introduces non-locality into linear kinetics and is central for understanding multi-stability and oscillations. 3. In the last part of the research, a hierarchical treatment of non-linear kinetic networks with a full account of number statistics relevant to single cell experiments is being developed. The projection operator is being explored as a formal technique to systematically reduce a complex kinetic network to a generic scheme with non-linear couplings.The work is having a broader impact through application of the resulting methods to complx reaction networks of interets in biology. Student training is also being positively impacted and Cao is making an effort to further disseminate the results of his research through a course he is developing for the Telluride Workshop.

马萨诸塞州技术研究所的江宫曹得到了一项小型赠款，用于从理论和计算化学研究计划中进行探索性研究，以开发一种将复杂的化学反应分解为不可恢复的方案的方法，该方案为一类反应提供了通用结构，并且是对子发现的变化的不变性。不可还原通用方案的概念有助于对动态行为的分析和分类，并促进了实验测量的解释。工作包括三个阶段。 1。通过识别两个动力学基序，即顺序链反应和分支反应，可以分解一阶动力学网络。然后，研究人员可以系统地串联链反应和侧支，可以减少对其通用形式的复杂反应，每个链接的每个链接代表与复杂的等待时间分布函数相关的子检查。当动力学步骤在子语言中发生变化时，等待时间分布函数会发生相应的变化，但是总体通用方案和相关的动态数量将保持相同的功能形式。 2。然后将高阶动力学网络围绕其稳态解决方案扩展到速率方程，该方程保留了平均浓度的动态行为中的全部非线性。稳态附近的相关性和波动通过解决方案的线性形式近似，这是一种与动态行为和响应测量的稳定性分析方法直接相关的方法。在线性化网络中，馈回或馈送机制定义了第三个基序，该基序将非局部性引入线性动力学，并且是理解多稳定性和振荡的核心。 3。在研究的最后一部分中，正在开发对具有与单细胞实验相关的数字统计数据的全文计算网络的层次处理。投影操作员正在作为一种形式技术进行探索，以系统地将复杂的动力学网络降低到具有非线性耦合的通用方案。这项工作通过应用所得的方法在生物学中的Inters中的反应反应网络而产生更大的影响。 学生培训也受到积极的影响，CAO正在努力通过他为Telluride研讨会开发的课程进一步传播他的研究结果。