Extended -Regular Sequence for Automated Analysis of Microarray Images
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Extended δ-Regular Sequence for Automated Analysis of Microarray Images Hee-Jeong Jin,1, 2 Bong-Kyung Chun,1, 2 and Hwan-Gue Cho1, 2 1 Department
of Computer Engineering, Pusan National University, San-30, Jangjeon-dong, Keumjeong-gu, Pusan, 609-735, South Korea 2 Research Institute of Computer, Information, and Communication, Pusan National University, San-30, Jangjeon-dong, Keumjeong-gu, Pusan, 609-735, South Korea Received 3 May 2005; Revised 24 August 2005; Accepted 1 December 2005 Microarray study enables us to obtain hundreds of thousands of expressions of genes or genotypes at once, and it is an indispensable technology for genome research. The first step is the analysis of scanned microarray images. This is the most important procedure for obtaining biologically reliable data. Currently most microarray image processing systems require burdensome manual block/spot indexing work. Since the amount of experimental data is increasing very quickly, automated microarray image analysis software becomes important. In this paper, we propose two automated methods for analyzing microarray images. First, we propose the extended δ-regular sequence to index blocks and spots, which enables a novel automatic gridding procedure. Second, we provide a methodology, hierarchical metagrid alignment, to allow reliable and efficient batch processing for a set of microarray images. Experimental results show that the proposed methods are more reliable and convenient than the commercial tools. Copyright © 2006 Hee-Jeong Jin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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INTRODUCTION
Microarray is a principal technology in molecular biology, because it results in hundreds and thousands of expressions of genotypes at once [1]. The microarrays are queried in a cohybridization assay using two or more fluorescently labeled probes prepared from the mRNA from the cellular phenotypes of interest [2]. The kinetics of hybridization allows expression levels to be determined relative to the ratio with which each probe hybridizes to an individual array element. Hybridization is assayed using a confocal laser scanner to measure fluorescence intensities, which allow the simultaneous determination of the relative level of expression of all the genes represented in the array. The first step of a microarray experiment is to generate a raw image, which consists of spots (genes) that form regular arrays (blocks). Figure 1 shows a typical microarray image which consists of 4 × 4 blocks and each block is composed of 24 × 24 spots [3]. In order to measure the level of expression of each spot, the location of each block and spot must be identified in a process called “gridding,” and then the area of each spot is determined. Finally, the intensity of both the true spot and the background is estimated; this is called “spots
quantification.” The gridding procedure must be performed cor
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