Zhang, L.S. and Kujis, J.N. and Liu, X.H. (2008) Information visualization for DNA microarray data analysis: A critical review. IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Reviews, 38 (1). pp. 42-54. ISSN 1094-6977.
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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 "abstract" 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.
|Uncontrolled keywords:||data analysis; gene expression; microarray; visualization|
|Subjects:||Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Q Science > QA Mathematics (inc Computing science)
|Divisions:||Faculties > Science Technology and Medical Studies > School of Computing|
|Depositing User:||Louise Dorman|
|Date Deposited:||03 Mar 2009 15:09|
|Last Modified:||04 Mar 2010 22:59|
|Resource URI:||http://kar.kent.ac.uk/id/eprint/15353 (The current URI for this page, for reference purposes)|
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