QSB: Computational and Experimental Studies of Pathways in Yeast

该项目的长期目标是调查一个框架，该框架可以提高对复杂生物路径的拓扑/连通性的理解。这项研究将实验分子遗传学和计算系统生物学相结合，开发了在真核细胞中定位复杂信号转导途径的新方法。最初的研究系统是发芽酵母中的Ras和Tor途径。这项研究将使用来自全基因组表达分析的数据集来开发和验证路径图。这项研究将集中在三个分析途径上：(1)研究使用大量DNA微阵列数据的遗传上位性分析方法，以定义途径的定性连接图；(2)研究基于超结构表示和混合整数线性优化框架的新的计算系统方法，以预测复杂途径的拓扑；(3)研究模型不确定性对代谢途径网络拓扑影响的定量分析框架。

The long range goal of this project is to investigate a framework that can improve understanding of the topology/connectivity of complex biological pathways. This research combines experimental molecular genetics with computational systems biology to develop new approaches for mapping complex signal transduction pathways in eukaryotic cells. The initial system for study is the Ras and Tor pathways in the budding yeast Saccharomyces cerevisiae. The research will employ data sets from whole genome expression analysis to develop and validate the pathway map. The research will focus on three avenues of analysis with the objectives: (1) to study a genetic epistasis analysis approach using extensive DNA microarray data to define a qualitative connectivity map of the pathways, (2) investigate a new computational systems approach based on a superstructure representation and a mixed integer linear optimization framework for the prediction of the topology of the complex pathways, and (3) study a quantitative analysis framework for the effect of model uncertainty on the network topology of the metabolic pathways.