Abstract
Complementary DNA (cDNA) microarray imaging technology is a revolutionary innovation for genomic research that allows monitoring of expression levels for thousands of genes simultaneously. The raw data of the cDNA microarray is shown as red and green channel images that are quantitatively analyzed to obtain the gene expression measurements. It can affect the subsequent analysis such as identification of genes differentially expressed. A cDNA microarray image analysis includes three tasks: image filtering, segmentation, and information extraction. This chapter presents a new segmentation method based on the expectation maximization (EM) algorithm and a new background and foreground segmentation correction method for an accurate information extraction. The advantage of our method is that there is no restriction on the spot shape within DNA microarray. The result of the experiment shows its robustness and precision.
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Acknowledgment
This work was supported by the Natural Science Foundation of Jiang Su Province (No. 08KJB510020) and the Natural Science Foundation of Suzhou (SYJG0934).
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Guirong, W. (2012). Microarray Denoising Using the Expectation Maximization Algorithm and Statistical Analysis. In: Chen, R. (eds) 2011 International Conference in Electrics, Communication and Automatic Control Proceedings. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-8849-2_42
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DOI: https://doi.org/10.1007/978-1-4419-8849-2_42
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