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An Effective Automated Method for the Detection of Grids in DNA Microarray

  • P. K. Srimani
  • Shanthi Mahesh
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 249)

Abstract

Microarray is a technology which allows biologists to potentially monitor the activity of all the genes of an organism. Microarrays, widely recognized as the next revolution in molecular biology, enables scientists to analyze genes, proteins and other biological molecules on a genomic scale. Image processing is the first step in knowledge discovery from the microarray. The process of extracting features consists of three stages: gridding, segmentation and quantification. Gridding is to assign each spot with individual coordinates. This paper presents a fully automatic grid configuration algorithm for detecting the microarray image spots as input, and makes no assumptions about the size of the spots, and number of rows and columns in the grid. The approach is based on the detection of an optimum sub image. This method is capable of processing the image automatically and does not demand any input parameters. Experimental result shows that this method is highly efficient method of gridding that uses intensity projection profile.

Keywords

Microarray Gridding Spot Intensity Expression Level Segmentation 

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References

  1. 1.
    Wu, S., Yan, H.: Microarray image processing based on clustering and morphological analysis. In: Proceedings of the First Asia-Pacific Bioinformatics Conference on sBioinformatics 2003, vol. 19, pp. 111–118 (2003)Google Scholar
  2. 2.
    Draghici, S.: Data Analysis Tools for DNA Microarrays. Chapman and Hall/CRC (2003)Google Scholar
  3. 3.
    M. Schena Microarray Analysis. Wiley-Liss (2002)Google Scholar
  4. 4.
    DeRisi, J.L., Iyer, V.R., Brown, P.O.: Exploring the metaboblic and genetic control of gene expression on a genomic scale. Science 278, 680–686 (1997)CrossRefGoogle Scholar
  5. 5.
    Schena, M., Shalom, D., Davis, R., Brown, P.: Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 270, 467–470 (1995), Stekel, D.: Microarray bioinformatics. Cambridge University Press, Cambridge (2003), Bowtell, D., Sambrook, J.: DNA microarrays: A molecular cloning manual. Cold Spring Harbor Laboratory Press (2003)Google Scholar
  6. 6.
    Rueda, L., Qin, L.: An Improved Clustering-Based Approach for DNA Microarray Image Segmentation. In: Campilho, A.C., Kamel, M.S. (eds.) ICIAR 2004. LNCS, vol. 3212, pp. 17–24. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  7. 7.
    Ceccarelli, M., Petrosino, A.: The Orientation Matching Transform Approach to Circular Object Detection. In: Proceedings of IEEE International Conference on Image Processing, pp. 712–715 (2001)Google Scholar
  8. 8.
    Anandhavalli, M., Mishra, C., Ghose, M.K.: Analysis of Microarray Image Spot Intensity: A Comparative Study. International Journal of Computer Theory and Engineering 1(5), 1793–8201 (2009)Google Scholar
  9. 9.
    Larese, M.G., Gomez, J.C.: Automatic Spot Addressing in cDNA Microarray Images. JCS&T 8(2) (July 2008)Google Scholar
  10. 10.
    Deepa, J., Thomas, T.: Automatic Gridding of DNA Microarray Images Using Optimum Sub-image. International Journal of Recent Trends in Engineering 1(4) (May 2009)Google Scholar
  11. 11.
    Deepa, J., Thomas, T.: A New Gridding Technique for High Density Microarray Images Using Intensity Projection Profile of Best Sub Image. Computer Engineering Intelligent Systems 4(1) (2013) ISSN 2222-1719Google Scholar
  12. 12.
    Rueda, L., Rezaeian, I.: A Fully automatic gridding method for cDNA microarray images. BMC Bioinformatics (April 21, 2011)Google Scholar
  13. 13.
    Labib, F.E.-Z., Fouad, I., Mabrouk, M., Sharawy, A.: An Efficient Fully Automated Method for Gridding Microarray Images. American Journal of Biomedical Engineering 2(3), 115–119 (2012)CrossRefGoogle Scholar
  14. 14.
    Sorin, D.: Data analysis tool for DNA Microarrays. Mathematical biology and medicine series. Chapman&Hall/CRC, London (2003)Google Scholar
  15. 15.
    Stekel, D.: MicroarrayBioinformatics. Cambridge University Press, NewYork (2003)Google Scholar
  16. 16.
    Lonardi, S., Luo, Y.: Gridding of microarray images. In: Proceedings of IEEE Computational Systems Bioinformatics Conferences, CSB 2004 (2004), doi:0-7695-2194-0/04Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • P. K. Srimani
    • 1
  • Shanthi Mahesh
    • 2
  1. 1.Dept. of Computer Science & MathsBangalore University, Director R&DBU. BangaloreIndia
  2. 2.Dept. of Information Science & EngineeringAtria Institute of TechnologyBangaloreIndia

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