Uncovering differentially expressed pathways with protein interaction and gene expression data

摘要：

The identification of genes and pathways involved in biological processes is a central problem in systems biology. Recent microarray technologies and other high-throughput experiments provide information which sheds light on this problem. In this article, we propose a new method to identify differentially expressed pathways via integration of gene expression and interactomic data in a sophisticated and efficient manner. Specifically, by using signal to noise ratio to measure the differentially expressed level of networks, this problem is modeled as a mixed integer linear programming problem (MILP). The results on yeast and human data demonstrate that the proposed method is more accurate and robust than previous ones.

关键词： Molecular interaction network gene expression pathway mixed integer linear programming signal to noise ratio.

作者: Yu-Qing Qiu Shihua Zhang Xiang-Sun Zhang

作者单位: Academy of Mathematics and Systems Science Chinese Academy of Sciences, Beijing 100190, China Gradua Academy of Mathematics and Systems Science Chinese Academy of Sciences, Beijing 100190, China

会议类型: 国际会议

会议名称: The Second International Symposium(OSB08)(第二届国际优化及系统生物学学术会议)

会议地点: 云南丽江

会议语种:英文

页码: 74-82

在线出版日期: 2008-10-31（万方平台首次上网日期，不代表论文的发表时间）