Abstract
In this paper we present a pipeline architecture specifically designed for processing of DNA microarray images. Many of the pixilated image generation methods produce one row of the image at a time. This property is fully exploited by a pipeline which takes in one row of the produced image at each clock pulse and performs the necessary image processing steps on it. This will remove the present need for sluggish software routines that are considered a major bottleneck in the microarray technology. The size of the proposed structure is a function of the width of the image and not its length. The proposed architecture is proved to be highly modular, scalable and suited for a Standard Cell VLSI implementation.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
P.O. Brown and D. Botstein, “Exploring the New World of the Genome with DNA Microarrays,” Nature Genetics,vol. 21, 1999, pp. 33–37.
M.K. Szczepanski, et al., “Enhancement of the DNAMicroarray Chip Images,” in Proceedings of the 14th International Conference on Digital Signal Processing, 2002, vol. 1, pp. 395–398.
O. Alter, P.O. Brown, and D. Botstein, “Generalized Singular Value Decomposition for Comparative Analysis of Genome-Scale Expression Data Sets of two Different Organisms,” in Proceedings of National Academy of Science, USA., 2003, vol. 100, no. 6, pp. 3351–3356.
P. Arena, L. Fortuna, and L. Occhipinti, “DNA Chip Image Processing via Cellular Neural Networks,” in Proceedings of the IEEE International Symposium on Circuits and Systems, 2001, vol. 3, pp. 345–348.
J.T. Smith and W.M. Reichert, “The Optimization of Quill-Pin Printed Protein and DNA Microarrays,” in Proceedings of the Second Joint EMBS/BMES Conference, 2002, vol. 2, pp. 1630–1631.
M.K. Szczepanski, et al., “Enhancement of the DNAMicroarray Chip Images,” in Proceedings of the 14th International Conference on Digital Signal Processing, 2002, vol. 1, pp. 395–398.
Xin-Yun Zhang, et al., “Signal Processing Techniques in Genomic Engineering,” in Proceedings of the IEEE, 2002, vol. 90, no. 12, pp. 1822–1833.
D.E. Bassett, M.B. Eisen, and M.S. Boguski, “Gene Expression Informatics–It's All in Your Mine,” Nature Genetics Supplement, vol. 21, 1999, pp. 51–55.
P. Arena, L. Fortuna, and L. Occhipinti, “A CNN Algorithm for Real Time Analysis of DNA Microarrays,” IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, vol. 49, no. 3, 2002, pp. 335–340.
P. Arena, M. Bucolo, L. Fortuna, and L. Occhipinti, “Cellular Neural Networks for Real-Time DNA Microarray Analysis,” IEEE Engineering in Medicine and Biology Magazine,vol. 21, no. 2, 2002, pp. 17–25.
M.L. Schmatz, “High-Speed and High-Density Chip-to-Chip Interconnections: Trends and Techniques,” IEEE Conference on Electrical Performance of Electronic Packaging, 2000, pp. 23–24.
S. Samavi, S. Shirani, and N. Karimi, “A Pipeline Structure for Analysis of DNA Microarrays,” in Proceedings of IEEE Pacific Rim Conference, 2003, pp. 1012–1015.
F. Azuaje, “Making Genome Expression Data Meaningful: Prediction and Discovery of Classes of Cancer through a Connectionist Learning Approach,” in Proceedings of IEEE International Symposium on Bio-Informatics and Biomedical Engineering, 2000, pp. 208–213.
C. Uehara and I. Kakadiaris, “Towards Automatic Analysis of DNA Microarrays,” in Proceedings of the Sixth IEEE Workshop on Applications of Computer Vision, 2002, pp. 57–62.
R.T. Koehler, et al., “Distributions of Free Energy, Melting Temperature, and Hybridization Propensity for Genomic DNA Oligomers,” in Proceedings of the, 2002, IEEE Computer Society Bioinformatics Conference, 2002, p. 337.
R. Hirata Jr. et al., “Microarray Gridding by Mathematical Morphology,” in Proceedings of XIV Brazilian Symposium on Computer Graphics and Image Processing, 2001, pp. 112–119.
Yuh-Jyh Hu, “Analyzing Gene Behaviors with Genetic Computation,” in Proceedings of Fourth International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies, 2000, vol. 2, pp. 776–779.
R. Gonzalez and R. Woods, Digital Image Processins, 2nd edn. Prentice Hall Book Company, 2002.
J. Hennesy and D. Patterson, Computer Architecture: A Quantitative Approach, 3rd edn. Morgan Kaufman Book Company, 2002.
http://cmgm.stanford.edu/pbrown/yeastchip.html.
S.J. Brignac, et al., “A Proximal CCD Imaging System for High-Throughput Detection of Microarray-Based Assays,” IEEE Engineering in Medicine and Biology Magazine,vol. 18, no. 2, 1999, pp. 120–122.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Samavi, S., Shirani, S., Karimi, N. et al. A Pipeline Architecture for Processing of DNA Microarrays Images. The Journal of VLSI Signal Processing-Systems for Signal, Image, and Video Technology 38, 287–297 (2004). https://doi.org/10.1023/B:VLSI.0000042493.11467.64
Published:
Issue Date:
DOI: https://doi.org/10.1023/B:VLSI.0000042493.11467.64