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KMID : 1132720070050030124
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Genomics & Informatics
2007 Volume.5 No. 3 p.124 ~ p.128
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PathTalk: Interpretation of Microarray Gene-Expression Clusters in Association with Biological Pathways
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Chung Tae-Su
Chung Hee-Joon
Kim Ju-Han
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Abstract
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Microarray technology enables us to measure the expression of tens of thousands of genes simultaneously under various
experimental conditions. Clustering analysis is one of the most successful methods for analyzing microarray data using
the assumption that co-expressed genes may be co-regulated. It is important to extract meaningful clusters from a long
unordered list of clusters and to evaluate the functional homogeneity and heterogeneity of clusters. Many quality
measures for clustering results have been suggested in different conditions. In the present study, we consider biological pathways as a collection of biological knowledge and used them as a reference for measuring the quality of clustering results and functional homogeneities. PathTalk visualizes and evaluates functional relationships between gene clusters and biological pathways.
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KEYWORD
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Microarray, Cluster analysis, evaluation, biological pathways
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