QSB: Discrete Optimization Techniques for Probing the Performance Limits of Metabolic Networks

拟议工作的目的是扩大线性和其他网络分析工具的使用。将寻求在模型约束中添加逻辑信息，以模仿监管逻辑。混合整数线性规划将是使用的工具之一。将使用两种一般方法。第一种方法需要对检查进行编码，以查看通量溶液是否与网络的动力学和调节结构一致。第二个涉及在概率框架内叠加来自DNA阵列的转录率数据，这解释了转录物水平和基因产物活性之间缺乏线性关系。

The aim of the proposed work is to extend the use of linear and other network analysis tools. The addition of logical information in model constraints to emulate regulatory logic will be pursued. Mixed integer linear programming will be among the tools employed. Two general approaches will be used. The first entails encoding a check to see if a flux solution is consistent with the kinetic and regulatory structure of the network. The second involves superimposing transcript ratio data from DNA arrays within probabilistic framework that account for the lack of linearity between transcript level and gene product activity.