Abstract
Cluster analysis has been widely used to explore thousands of gene expressions from microarray analysis and identify a small number of similar genes (objects) for further detailed biological investigation. However, most clustering algorithms tend to identify loose clusters with too many genes. In this paper, we propose a Bayesian tight clustering method for time course gene expression data, which selects a small number of closely-related genes and constructs tight clusters only with these closely-related genes.
Original language | English |
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Pages (from-to) | 17-38 |
Number of pages | 22 |
Journal | Computational Statistics |
Volume | 25 |
Issue number | 1 |
DOIs | |
State | Published - Mar 2010 |
Keywords
- Bayesian cluster analysis
- Microarray
- Tight clustering
- Time course gene expression