Please use this identifier to cite or link to this item:
Title: Information visualization for DNA microarray data analysis: A critical review
Authors: Zhang, L
Kuljis, J
Liu, X
Keywords: DNA;Biology computing;Data analysis;Data visualisation
Issue Date: 2008
Publisher: IEEE
Citation: IEEE Transactions on Systems, Man and Cybernetics - Part C , 38(1): 42-54. Jan 2008
Abstract: Graphical representation may provide effective means of making sense of the complexity and sheer volume of data produced by DNA microarray experiments that monitor the expression patterns of thousands of genes simultaneously. The ability to use ldquoabstractrdquo graphical representation to draw attention to areas of interest, and more in-depth visualizations to answer focused questions, would enable biologists to move from a large amount of data to particular records they are interested in, and therefore, gain deeper insights in understanding the microarray experiment results. This paper starts by providing some background knowledge of microarray experiments, and then, explains how graphical representation can be applied in general to this problem domain, followed by exploring the role of visualization in gene expression data analysis. Having set the problem scene, the paper then examines various multivariate data visualization techniques that have been applied to microarray data analysis. These techniques are critically reviewed so that the strengths and weaknesses of each technique can be tabulated. Finally, several key problem areas as well as possible solutions to them are discussed as being a source for future work.
ISSN: 1552-3098
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

Files in This Item:
File Description SizeFormat 
04383143.pdf1.22 MBAdobe PDFView/Open

Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.