Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/23311
Title: Biclusters visualization and detection using parallel coordinate plots
Authors: Cheng, KO
Law, NF 
Siu, WC 
Liew, AWC
Keywords: Biclustering
Bioinformatics
Clustering
Gene expression data analysis
Issue Date: 2007
Source: AIP Conference Proceedings, 2007, v. 952, p. 114-123 How to cite?
Journal: AIP Conference Proceedings 
Abstract: The parallel coordinate (PC) plot is a powerful visualization tools for high-dimensional data. In this paper, we explore its usage on gene expression data analysis. We found that both the additive-related and the multiplicative-related coherent genes exhibit special patterns in the PC plots. One-dimensional clustering can then be applied to detect these patterns. Besides, a split-and-merge mechanism is employed to find the biggest coherent subsets inside the gene expression matrix. Experimental results showed that our proposed algorithm is effective in detecting various types of biclusters. In addition, the biclustering results can be visualized under a 2D setting, in which objective and subjective cluster quality evaluation can be performed.
Description: 2007 International Symposium on Computational Models for Life Sciences, CMLS '07, Gold Coast, QLD, 17-19 December 2007
URI: http://hdl.handle.net/10397/23311
ISBN: 9780735404663
ISSN: 0094-243X
DOI: 10.1063/1.2816614
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