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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.

Record type: Conference or Workshop Item (Paper)


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.

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Published date: September 2009
Additional Information: Event Dates: September 2009
Venue - Dates: Pattern Recognition in Bioinformatics, 2009-09-01
Organisations: Southampton Wireless Group


Local EPrints ID: 268188
ISBN: 978-3-642-04030-6
PURE UUID: ecd4ec68-b0a9-4ef7-b57b-f423b4b66023

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Date deposited: 11 Nov 2009 14:27
Last modified: 18 Jul 2017 06:56

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Author: Salih Tuna

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