Cross-Platform Analysis with Binarized Gene Expression Data

Tuna, Salih and Niranjan, Mahesan (2009) Cross-Platform Analysis with Binarized Gene Expression Data At Pattern Recognition in Bioinformatics. , pp. 439-449.


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With widespread use of microarray technology as a potential diagnostics tool, the comparison of results obtained from the use of different platforms is of interest. When inference methods are designed using data collected using a particular platform, they are unlikely to work directly on measurements taken from a different type of array. We report on this cross-platform transfer problem, and show that working with transcriptome representations at binary numerical precision, similar to the gene expression bar code method, helps circumvent the variability across platforms in several cancer classification tasks. We compare our approach with a recent machine learning method specifically designed for shifting distributions, i.e., problems in which the training and testing data are not drawn from identical probability distributions, and show superior performance in three of the four problems in which we could directly compare.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Event Dates: September 2009
Venue - Dates: Pattern Recognition in Bioinformatics, 2009-09-01
Organisations: Southampton Wireless Group
ePrint ID: 268188
Date :
Date Event
September 2009Published
Date Deposited: 11 Nov 2009 14:27
Last Modified: 17 Apr 2017 18:37
Further Information:Google Scholar

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