Extended δ-regular sequence for automated analysis of microarray images

  • Authors:

  • Hee-Jeong Jin;Bong-Kyung Chun;Hwan-Gue Cho

  • Affiliations:

  • Department of Computer Engineering, Pusan National University, Jangjeon-dong, Keumjeong-gu, Pusan, South Korea and Research Institute of Computer, Information, and Communication, Pusan National Un ...;Department of Computer Engineering, Pusan National University, Jangjeon-dong, Keumjeong-gu, Pusan, South Korea and Research Institute of Computer, Information, and Communication, Pusan National Un ...;Department of Computer Engineering, Pusan National University, Jangjeon-dong, Keumjeong-gu, Pusan, South Korea and Research Institute of Computer, Information, and Communication, Pusan National Un ...

  • Venue:
  • EURASIP Journal on Applied Signal Processing
  • Year:
  • 2006

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Abstract

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.