Affiliation:
1. State University of New York at Buffalo
Abstract
Analyzing coherent gene expression patterns is an important task in bioinformatics research and biomedical applications. Recently, various clustering methods have been adapted or proposed to identify clusters of co-expressed genes and recognize coherent expression patterns as the centroids of the clusters. However, the interpretation of co-expressed genes and coherent patterns mainly depends on the domain knowledge, which presents several challenges for coherent pattern mining and cannot be solved by most existing clustering approaches.In this paper, we introduce an
interactive exploration
system
GeneX
(Gene eXplorer) for mining coherent expression patterns. We develop a novel
coherent pattern index graph
to provide highly confident indications of the existence of coherent patterns. Typical exploration operations are supported based on the index graph. We also provide a bunch of graphical views as the user interface to visualize the data set and facilitate the interactive operations. To help users to interpret and validate the mining results, we design the
gene annotation panel
that connects the genes with some public annotation databases. The experimental results show that our approach is more effective than the state-of-the-art methods in mining real gene expression data sets.
Publisher
Association for Computing Machinery (ACM)
Cited by
9 articles.
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