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    Obtaining quality microarray data via image reconstruction

    O'Neill, P. and Magoulas, George and Liu, X. (2003) Obtaining quality microarray data via image reconstruction. In: Berthold, M.R. and Lenz, H.-J. and Bradley, E. and Kruse, R. and Borgelt, C. (eds.) Advances in Intelligent Data Analysis V: 5th International Symposium on Intelligent Data Analysis. Lecture Notes in Computer Science 2810. Springer, pp. 364-375. ISBN 9783540408130.

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    Abstract

    This paper introduces a novel method for processing spotted microarray images, inspired from image reconstruction. Instead of the usual approach that focuses on the signal when removing the noise, the new method focuses on the noise itself, performing a type of interpolation. By recreating the image of the microarray slide, as it would have been with all the genes removed, the gene ratios can be calculated with more precision and less influence from outliers and other artefacts that would normally make the analysis of this data more difficult. The new technique is also beneficial, as it does not rely on the accurate fitting of a region to each gene, with its only requirement being an approximate coordinate. In experiments conducted the new method was tested against one of the mainstream methods of processing spotted microarray images. Our method is shown to produce much less variation in gene measurements. This evidence is supported by clustering results that show a marked improvement in accuracy.

    Metadata

    Item Type: Book Section
    School: School of Business, Economics & Informatics > Computer Science and Information Systems
    Depositing User: Sarah Hall
    Date Deposited: 29 Jun 2021 14:11
    Last Modified: 29 Jun 2021 14:11
    URI: https://eprints.bbk.ac.uk/id/eprint/44914

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