Skip to main content
SpringerLink
Log in
Book cover

Bioinformatics Technologies pp 353–388Cite as

Microarray Data Analysis

  • Chapter

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Akutsu, T., Miyano, S. and Kuhara, S. (2000) Inferring qualitative relations in genetic networks and metabolic pathways. Bioinformatics 16: 727–734.

    Article  Google Scholar 

  • Alon, U., Barkai, N., Notterman, D.A., Gish, K., Ybarra, S., Mack, D. and Levine, A.J. (1999) Gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays. Proc. Nat. Acad. Sci. USA. 96: 6745–6750.

    Article  Google Scholar 

  • Alter, O., Brown, P.O., Botstein, D. (2000) Singular value decomposition for genome-wide expression data processing and modeling. Proc. Nat. Acad. Sci. USA. 97: 10101–10106.

    Article  Google Scholar 

  • Axon Instruments Inc. GenePix Pro 3. 0, 2001.

    Google Scholar 

  • Brazma,, A. and Vilo, J. (2000) Minireview: Gene expression data analysis. European Molecular Biology Laboratory, Outstation Hinxton-the European Bioinformatics institute, Cambridge CB10 ISD UK.

    Google Scholar 

  • Buckley, M. (2002) The Spot User’s Guide. CSIRO Mathematical and Information Sciences, Australia. http://www.cmis.csiro.au/iap/spot.htm.

    Google Scholar 

  • Buhler, J., Ideker, T., Haynor, D. (2000) Dapple: Improved Techniques for Finding Spots on DNA Microarrays. Technical Report UWTR 2000-08-05, University of Washington.

    Google Scholar 

  • Butte, A.J., Tamayo, P., Slonim, D., Golub, T.R., and Kohane, I.S. (2000). Discovering functional relationships between RNA expression and chemotherapeutic susceptibility using relevance networks. Proc. Nat. Acad. Sci. USA. 97(22): 12182–12186.

    Article  Google Scholar 

  • Chen, T., He, H.L., Church, G.M. (1999) Modeling gene expression with differential equations. Pacific Symposium on Biocomputing 4: 29–40.

    Google Scholar 

  • Chen, T., Filkov, V. and Skiena, S.S. (1999) Identifying gene regulatory networks from experimental data. Proceedings of the Third Annual International Conference on Computational Molecular Biology RECOMB99, Lyon, France, March 1999, pp 94–103.

    Google Scholar 

  • Chen, Y., Dougherty, E.R. and Bittner, M.L. (1997) Ratio-based decisions and the Quantitative Analysis of cDNA Microarray Images. J. Biomedical Optics. 2: 364–374.

    Google Scholar 

  • Chu, S., DeRisi, J., Eisen, M., Mulholland, J., Botstein, D., Brown, P.O. and Herskowitz, I. (1998) The transcriptional program of sporulation in budding yeast. Science 282(5389): 699–705

    Article  Google Scholar 

  • Clausi, D.A. (2002). K-means Iterative Fisher (KIF) unsupervised clustering algorithm applied to image texture segmentation. Pattern Recognition 35: 1959–1972.

    Article  MATH  Google Scholar 

  • D’Haeseleer, P., Wen, X., Fuhrman, S. and Somogyi, R. (1999) Linear modeling of mRNA expression levels during CNS development and injury. Pacific Symposium on Biocomputing 4: 41–52.

    Google Scholar 

  • D’Haeseleer, P., Liang and S., Somogyi, R. (2000) Genetic network inference: from co-expression clustering to reverse engineering. Bioinformatics 16(8): 707–726.

    Google Scholar 

  • DeRisi, J.L., Lyer, V.R. and Brown, P.O. (1997) Exploring the metabolic and genetic control of gene expression on a genomic scale. Science 278: 680–686.

    Article  Google Scholar 

  • Duda, R.O., Hart, P.E. and Stork, D.G. (2001). Pattern Classification. Wiley-Interscience, NewYork.

    Google Scholar 

  • Eisen, M. (1999) ScanAlyze User Manual. Stanford University. http://rana.lbl.gov/EisenSoftware.htm.

    Google Scholar 

  • Eisen, M.B., Spellman, P.T., Brown, P.O. and Botstein, D. (1998) Cluster analysis and display of genome-wide expression patterns. Proc. Nat. Acad. Sci. USA. 95: 14863–14868.

    Article  Google Scholar 

  • Filkov, V., Skiena, S. and Zhi, J. (2002) Analysis Techniques for microarray time series data. J. Comp. Biol. 9(2): 317–330.

    Google Scholar 

  • Friedman, N., Linial, M., Nachman, I. and Pe’er, D. (2000) Using Bayesian network to analyze expression data. J. Comp. Biol., 7: 601–620.

    Google Scholar 

  • Glass, L. (1975) Combinatorial and topological methods in nonlinear chemical kinetics. J. Chem. Phys. 63(4): 1325–1335.

    Article  Google Scholar 

  • Glass, L. and Pasternack, J.S. (1978) Stable oscillations in mathematical models of biological control systems. J. Math. Biol. 6: 207–223.

    MathSciNet  Google Scholar 

  • Golub, T.R., Slonim, D.K., Tamayo, P., Huard, C., Gaasenbeek, M., Mesirov, J.P., Coller, H., Loh, M.L., Downing, J.R., Caligiuri, M.A., Bloomfield, C.D. and Lander, E.S. (1999) Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring. Science 286: 531–537.

    Article  Google Scholar 

  • Hartemink, A.J., Gifford, D.K., Jaakkola, T.S. and Young, R.A. (2002) Combining location and expression data for principled discovery of genetic regulatory network models. Pacific Symposium on Biocomputing 7: 437–449.

    Google Scholar 

  • Imoto, S., Goto, T. and Miyano, S. (2002a) Estimation of genetic networks and functional structures between genes by using Bayesian networks and nonparametric regression. Pacific Symposium on Biocomputing 37: 175–186.

    Google Scholar 

  • Imoto, S., Kim, S., Goto, T., Aburatani, S., Tashiro, K., Kuhara, S. and Miyano, S. (2002b) Bayesian network and nonparametric heteroscedastic regression for nonlinear modeling of genetic network. Journal of Bioinformatics and Computational Biology, in press. (Preliminary version has appeared in Proc. 1st IEEE Computer Society Bioinformatics Conference, 219–227, 2002).

    Google Scholar 

  • Holter, N.S., Mitra, M., Maritan, A., Cieplak, M., Banavar, J.R. and Fedoroff, N.V. (2000) Fundamental patterns underlying gene expression profiles: Simplicity from complexity. Proc. Nat. Acad. Sci. USA. 97: 8409–8414.

    Article  Google Scholar 

  • Huang, S. (1999) Gene expression profiling, genetic networks, and cellular states: an integrating concept for tumorigenesis and drug discovery. J. Mol. Med. 77: 469–480.

    Google Scholar 

  • Iyer, V.R., Eisen, M.B., Ross, D.T., Schuler, G., Moore, T., Lee, J.C.F. and Trent, J.M., Staudt, L.M., Hudson, Jr. J., Boguski, M.S., Lashkari, D., Shalon, D., Botstein, D. and Brown, P.O. (1999) The transcriptional program in the response of human fibroblasts to serum. Science 283(5398): 83–97.

    Article  Google Scholar 

  • Kauffman, S.A. (1969) Metabolic stability and epigenesist in randomly connected nets. J. Theor. Biol. 22: 437–467.

    Article  MathSciNet  Google Scholar 

  • Kauffman, S.A. (1993) The origin of order: Self-organization and selection in evolution. Oxford University Press, New York.

    Google Scholar 

  • Kooperberg, C., Fazzio, T.G., Delrow, J.J. and Tsukiyama, T. (2002) Improved background correction for spotted DNA microarrays. J. Comp. Biol. 9(1): 55–66.

    Google Scholar 

  • Kwon, A. T, Hoos, H.H. and Ng, R. (2003) Inference of transcriptional regulation relationships from gene expression data. Bioinformatics 19(8): 905–912.

    Article  Google Scholar 

  • Liebermeister, W. (2002) Linear modes of gene expression determined by independent component analysis. Bioinformatics 18(1): 51–60.

    Article  Google Scholar 

  • Liew, A.W.C., Yan, H. and Yang, M. (2003a) Robust Adaptive Spot Segmentation of DNA Microarray Images. Pattern Recognition 36(5): 1251–1254.

    Google Scholar 

  • Liew, A.W.C., Szeto, L.K., Tang, S.S. and Yan, H. (2003b) A computational approach to gene expression data extraction and analysis. To appear in special issue on “Genomic Signal Processing”. J. VLSI Signal Processing-Systems for Signal, Image, and Video Technology.

    Google Scholar 

  • Lockhart, D.J. and Winzeler, E.A. (2000) Genomics, gene expression and DNA arrays. Nature 405: 827–846.

    Article  Google Scholar 

  • Marnellos, G., Mjolsness, E. (1998) A gene network approach to modeling early neurogenesis in Drosophila. Pacific Symposium on Biocomputing 3: 30–41.

    Google Scholar 

  • Marnellos, G., Deblandre, G.A., Mjolsness, E. and Kintner, C. (2000) Delta-Notch lateral inhibitory patterning in the emergence of ciliated cells in Xenopus: experimental observations and a gene network model. Pacific Symposium on Biocomputing 5: 329–340.

    Google Scholar 

  • Marple, S. (1987) Digital Spectral Analysis with Applications. Prentice Hall Inc., Englewood Cliffs, New Jersey.

    Google Scholar 

  • Moore, S.K. (2001). Making Chips to probe genes. IEEE Spectrum, March 2001, pp. 54–60.

    Google Scholar 

  • Packard BioChip Technologies, LLC QuantArray Microarray Analysis Software

    Google Scholar 

  • Perou, C.M., Jeffrey, S.S., van de Rijn, M., Rees, C.A., Eisen, M.B., Ross, D.T., Pergamenschikov, A., Williams, C.F., Zhu, S.X., Lee, J.C.F., Lashkari, D., Shalon, D., Brown, P.O. and Botstein, D. (1999) Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. Proc. Nat. Acad. Sci. USA. 96: 9212–9217.

    Article  Google Scholar 

  • Sambrook, J. and Russell, D.W. (2001) Molecular Cloning: A Laboratory Manual. 3rd Ed., Cold Spring Harbor Laboratory Press, New York.

    Google Scholar 

  • Schena, M., Shalon, D., Davis, R.W. and Brown, P.O. (1995) Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 270: 467–470.

    Google Scholar 

  • Shmulevich, I., Dougherty, E.R. and Zhang, W. (2002a) From Boolean to probabilistic Boolean networks as models of genetic regulatory networks. Proc. IEEE 90(11): 1778–1792.

    Article  Google Scholar 

  • Shmulevich, I., Dougherty, E.R., Kim, S. and Zhang, W. (2002b) Probablistic Boolean networks: a rule-based uncertainty model for gene regulatory networks. Bioinformatics 18: 261–274.

    Google Scholar 

  • Spellman, P.T., Sherlock, G., Zhang, M.Q., Iyer, V.R., Anders, K., Eisen, M.B., Brown, P.O., Botstein, D. and Futcher, B. (1998) Comprehensive Identification of Cell Cycle-regulated Genes of the Yeast Saccharomyces cerevisiae by Microarray Hybridization. Molecular Biology of the Cell 9: 3273–3297.

    Google Scholar 

  • Szallasi, Z. and Liang, S. (1998) Modeling the normal and neoplastic cell cycle with realistic Boolean genetic networks: their application for understanding carcinogenesis and assessing therapeutic strategies. Pacific Symposium on Biocomputing 3: 66–76.

    Google Scholar 

  • Szeto, L.K., Liew, A.W.C., Yan, H. and Tang, S.S. (2003) Gene expression data clustering and visualization based on a binary hierarchical clustering framework. J. Vis. Lang. Computing 14: 341–362.

    Google Scholar 

  • Tamayo, P., Slonim, D., Mesirov, J., Zhu, Q., Kitareewan, S., Dmitrovsky, E., Lander, E.S. and Golub, T.R. (1999) Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoietic differentiation. Proc. Nat. Acad. Sci. USA. 96: 2907–2912.

    Article  Google Scholar 

  • Tang, C., Zhang, L. and Zhang, A. (2002) Interactive visualization and analysis for gene expression data. IEEE Proceedings of the Hawaii International Conference on System Sciences. Big Island, HI. January 2002. 6: 143–166.

    Google Scholar 

  • Thieffry, D. and Thomas, R. (1998) Qualitative analysis of gene networks. Pacific Symposium on Biocomputing 3: 77–88.

    Google Scholar 

  • Thomas, R. (1991) Regulatory networks seen as asynchronous automata: a logical description. J. Theor. Biol. 153: 1–23.

    Google Scholar 

  • Troyanskaya, O., Cantor, M., Sherlock, G., Brown, P., Hastie, T., Tibshirani, R., Botstein, D., and Altman, R.B. (2001) Missing values estimation methods for DNA microarrays. Bioinformatics 17: 520–525.

    Article  Google Scholar 

  • Vohradsky, J. (2001a) Neural model of the genetic network. J. Biol. Chem. 276: 36168–36173.

    Article  Google Scholar 

  • Vohradsky, J. (2001b) Neural network model of gene expression. Faseb J. 15: 846–854.

    Article  Google Scholar 

  • Vu, T.T., Vohradsky, J. (2002) Genexp — a genetic network simulation environment. Bioinformatics 18(10): 1400–1401.

    Article  Google Scholar 

  • Wang, X., Ghosh, S. and Guo, S.W. (2001) Quantitative Quality Control in Microarray Image Processing and Data Acquisition. Nucl. Acids Res. 29(15): e75.

    Article  Google Scholar 

  • White, K.P., Rifkin, S.A., Hurban, P. and Hogness, D.S. (1999) Microarray analysis of Drosophila development during metamorphosis. Science 286: 2179–2184.

    Google Scholar 

  • Wolfinger, R.D., Gibson, G., Wolfinger, E.D., Bennett, L., Hamadeh, H., Bushel, P., Afshari, C. and Paules, R.S. (2001) Assessing gene significance from cDNA microarray expression data via mixed models. J. Comp. Biol. 8: 625–637.

    Google Scholar 

  • Wu, S., Liew, A.W.C., and Yan H. (2004). Cluster Analysis of Gene Expression Data Based on Self-Splitting and Merging Competitive Learning. IEEE Transactions on Information Technology in Biomedicine 8(1): 5–15.

    Article  Google Scholar 

  • Wuensche, A. (1999) Classifying cellular automata automatically: Finding gliders, filtering, and relating space-time patterns, attractor basins, and the Z parameter. Complexity 4(3): 47–66.

    Article  MathSciNet  Google Scholar 

  • Yeung, K.Y. and Ruzzo, W.L. (2001) Principal component analysis for clustering gene expression data. Bioinformatics 17(9): 763–774.

    Article  Google Scholar 

  • Yeung, L.K., Szeto, L.K., Liew, A.W.C. and Yan, H. (2003) Dominant spectral component analysis for transcriptional regulations using microarray timeseries data. To appear in Bioinformatics.

    Google Scholar 

  • Yang, Y.H., Dudoit, S., Luu, P., Lin, D.M., Peng, V., Ngai, J. and Speed, T.P. (2002) Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. Nucl. Acids Res. 30(4): e15.

    Article  Google Scholar 

  • Zhang, Y.J. and Liu, Z.Q. (2002) Self-Splittng competitive learning: A new online clustering paradigm. IEEE Trans. on neural networks 13: 369–380.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Engineering and Information Technology, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong

    Alan W. -C. Liew & Hong Yan

  2. School of Electrical and Information Engineering, University of Sydney, NSW, 2006, Australia

    Hong Yan

  3. Department of Biology and Chemistry, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong

    Mengsu Yang

  4. School of Information Technology, Deakin University, Australia

    Y. -P. Phoebe Chen

Authors
  1. Alan W. -C. Liew
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hong Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mengsu Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Y. -P. Phoebe Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Information Technology, Faculty of Science and Technology, Deakin University, Australia

    Yi-Ping Phoebe Chen

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Hiedelberg

About this chapter

Cite this chapter

Liew, A.W.C., Yan, H., Yang, M., Chen, Y.P.P. (2005). Microarray Data Analysis. In: Chen, YP.P. (eds) Bioinformatics Technologies. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-26888-X_12

Download citation

  • DOI: https://doi.org/10.1007/3-540-26888-X_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-20873-0

  • Online ISBN: 978-3-540-26888-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation