GenExplore: Interactive Exploration of Gene Interactions from Microarray Data

DNA Microarray provides a powerful basis for analysis of gene expression. Data mining methods such as clustering have been widely applied to microarray data to link genes that show similar expression patterns. However, this approach usually fails to unveil gene-gene interactions in the same cluster. In this project, we propose to combine graphical model based interaction analysis with other data mining techniques (e.g, association rule, hierarchical clustering) for this purpose. For interaction analysis, we propose the use of Graphical Gaussian Model to discover pairwise gene interactions and loglinear model to discover multi-gene interactions. We have constructed a prototype system that permits rapid interactive exploration of gene relationships; results can be validated by experts or known information, or suggest new experiments. We have tested our methodology using the yeast microarray data. Our results reveal some previously unknown interactions that have solid biological explanat...

• Type: Conference
• Year: 2004
• Where: ICDE
• Authors: Yong Ye, Xintao Wu, Kalpathi R. Subramanian, Liying Zhang
• Keywords: Database, Gene Interactions, Gene-gene Interactions, ICDE 2004, Yeast Microarray Data