Interactive exploration of coherent patterns in time-series gene expression data
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Towards interactive exploration of gene expression patterns
ACM SIGKDD Explorations Newsletter
Mining coherent gene clusters from gene-sample-time microarray data
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
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Discovering co-expressed genes and coherent expression patterns in gene expression data is an important data analysis task in bioinformatics research and biomedical applications. Although various clustering methods have been proposed, two tough challenges still remain on how to integrate the users' domain knowledge and how to handle the high connectivity in the data. Recently, we have systematically studied the problem and proposed an effective approach [3]. In this paper, we describe a demonstration of GPX (for Gene Pattern eXplorer), an integrated environment for interactive exploration of coherent expression patterns and co-expressed genes in gene expression data. GPX integrates several novel techniques, including the coherent pattern index graph, a gene annotation panel, and a graphical interface, to adopt users' domain knowledge and support explorative operations in the clustering procedure. The GPX system as well as its techniques will be showcased, and the progress of GPX will be exemplified using several real-world gene expression data sets.