Skip to main content
Log in

Biotechnology. Gene expression and microchips: Problems of the quantitative analysis

  • Published:
Russian Journal of General Chemistry Aims and scope Submit manuscript

Abstract

The technology of gene microchips that performed a real revolution in the investigation of the genetic system [1] affected the development of many medical and biological branches of science, including oncology [2, 3], toxicology [4], pharmacology [5], biology of development [6], facilitated the solution of classical problems of molecular biology concerning the study of gene mutations and transcription mechanisms [7, 8]. In contrast to the traditional approach of the molecular genetics, like the methods based on the polymerase chain reaction (PCR), Nothern-blotting and the subsequent analysis of the gene expression [9–11], addressed to the study of expression of a single or few genes, the microchips made it possible to carry out simultaneous monitoring of the expression of the whole cell genome under strictly controlled conditions. This monitoring provides a possibility to reveal the strategies used by the cell in response to the change in the external conditions, to establish the groups of genes functionally connected, to reconstruct the mechanisms of transcription regulation and to determine the metabolic ways connected thereto, to analyze the genes whose function in the cell remained unknown.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Elvidge, G., Pharmacogenomics, 2006, vol. 7, p. 123.

    Article  CAS  Google Scholar 

  2. Golub, T.R., Slonim, O.K., Tamayo P., et al., Science, 1999, vol. 286, p. 531.

    Article  CAS  Google Scholar 

  3. Alon, U., Barkai, N., Notterman, D.A., et al., Proc. Natl. Acad. Sci. USA, 1999, vol. 96, p. 6745.

    Article  CAS  Google Scholar 

  4. Shioda, T.J., Environ, Pathol. Toxicol. Oncol., 2004, vol. 23, p. 13.

    Article  CAS  Google Scholar 

  5. Debouck, C. and Goodfellow, P.N., Nat. Genet. Suppl., 1999, vol. 21, p. 48.

    Article  CAS  Google Scholar 

  6. Robson, P., Trends Biotechnol., 2004, vol. 22, p. 609.

    Article  CAS  Google Scholar 

  7. Pappas, C.T., Sram, J., Moskvin, O.V., et al., J. Bacteriol., 2004, vol. 186, p. 4748.

    Article  CAS  Google Scholar 

  8. Hacia, J., Nat. Genet. Suppl., 1999, vol. 21, p. 42.

    Article  CAS  Google Scholar 

  9. Saiki, R.K., Bugawan, T.L., Horn, G.T., et al., Nature, 1986, vol. 324, p. 163.

    Article  CAS  Google Scholar 

  10. Alwine, J.C., Kemp, D.J., and Stark, G.R., Proc. Natl. Acad. Sci. USA, 1977, vol. 74, p. 5350.

    Article  CAS  Google Scholar 

  11. Velculescu, V.E., Zhang, L., Vogelstein, B., et al., Science, 1995, vol. 270, p. 484.

    Article  CAS  Google Scholar 

  12. Schena, M., Shalon, D., Davis, R.W., et al., Ibid., 1995, vol. 270, p. 467.

    Article  CAS  Google Scholar 

  13. Duggan, D.J., Bittner, M., Chen, Y., et al., Nat. Genet. Suppl., 1999, vol. 21, p. 10.

    Article  CAS  Google Scholar 

  14. Hughes, T.R., Mao, M., Jones, A.R., et al., Nat. Biotechnol., 2001, vol. 19, p. 342.

    Article  CAS  Google Scholar 

  15. Lipshutz, R.J., Fodor, S.P., Gingeras, T.R., et al., Nat. Genet., 1999, vol. 21, p. 20.

    Article  CAS  Google Scholar 

  16. Blanchard, A.P., Kaiser, R.J., and Hood, L.E., Biosensors and Bioelectronics, 1996, vol. 11, p. 687.

    Article  CAS  Google Scholar 

  17. Maskos, U. and Southern, E.M., Nucl. Acids Res., 1993, vol. 21, p. 2267.

    Article  CAS  Google Scholar 

  18. Schena, M., Shalon, D., Heller, R., et al., Proc. Natl. Acad. Sci. USA, 1996, vol. 93, p. 10614.

    Article  CAS  Google Scholar 

  19. Evertsz, E.M., Au-Young, J., Ruvolo, M.V., et al., Biotechniques, 2001, vol. 31, p. 1182.

    CAS  Google Scholar 

  20. Murphy, D., Adv. Physiol. Educ., 2002, vol. 26, p. 256.

    Google Scholar 

  21. Schadt, E., Li, C., Su, C., et al., J. Cell Biochem., 2000, vol. 80, p. 192.

    Article  CAS  Google Scholar 

  22. Sebastiani, P., Gussoni, E., Kohane, I.S., et al., Statist Sci., 2003, vol. 18, p. 33.

    Article  Google Scholar 

  23. Yang, Y.H., Dudoit, S., Luu, P., et al., Nucl. Acids Res., 2002, vol. 30, p. e15.

    Article  Google Scholar 

  24. Li, C. and Wong, W., Proc. Natl. Acad. Sci. USA, 2001, vol. 98, p. 31.

    Article  CAS  Google Scholar 

  25. Irizarry, R.A., Hobbs, B., Colin, F., et al., Biostatistics, 2003, vol. 4, p. 249.

    Article  Google Scholar 

  26. Irizarry, R.A., Bolstad, B.M., Colin, F., et al., Nucl. Acids Res., 2003, vol. 31, p. e15.

    Article  CAS  Google Scholar 

  27. Quackenbush, J., Nat. Rev. Genet., 2001, vol. 2, p. 418.

    Article  CAS  Google Scholar 

  28. Rhodius, V., Van Dyk, T.K., Gross, C., et al., Annu. Rev. Micro-biol., 2002, vol. 56, p. 599.

    Article  CAS  Google Scholar 

  29. Dudoit, S., Yang, Y.H., Callow, M.J., et al., Statistica Sinica, 2002, vol. 12, p. 111.

    Google Scholar 

  30. Tseng, G.C., Oh, M.-K., Rohlin, L., et al., Nucl. Acids Res., 2001, vol. 29, p. 2549.

    Article  CAS  Google Scholar 

  31. Tusher, V.G., Tibshirani, R., and Chu, G., Proc. Natl. Acad. Sci. USA, 2001, vol. 98, p. 5116.

    Article  CAS  Google Scholar 

  32. Jiang, D., Tang, C., and Zhang, A., IEEE Trans. Knowl. Data Eng., 2004, vol. 16, p. 1370.

    Article  Google Scholar 

  33. Troyanskaya, O., Cantor, M., Sherlock, G., et al., Bioinformatics, 2001, vol. 17, p. 520.

    Article  CAS  Google Scholar 

  34. Kuruvilla, F.G., Park, P.J., and Schreiber, S.L., Genome Biol., 2002, vol. 3, p. 0011.

    Article  Google Scholar 

  35. Fambrough, D., McClure, K., Kazlauskas, A., et al., Cell, 1999, vol. 97, p. 727.

    Article  CAS  Google Scholar 

  36. Mills, J.C. and Gordon, J.I., Nucl. Acids Res., 2001, vol. 29, p. e72.

    Article  CAS  Google Scholar 

  37. Phang, T.L., Neville, M.C., Rudolph, M., et al., Pac. Symp. Biocomput., 2003, p. 351.

  38. Efron, B., Netraditsyonnye metody mnogomernogo statisticheskogo analiza (Nontraditional Methods of Multidimensional Statistical Analysis, Moscow: Finansy i statistika, 1988.

    Google Scholar 

  39. De Risi, J.L, Iyer, V.R., and Brown, P.O., Science, 1997, vol. 278, p. 680.

    Article  Google Scholar 

  40. Sabatti, C., Karsten, S.L, and Geschwind, D.H., Math. Biosci., 2002, vol. 176, p. 17.

    Article  CAS  Google Scholar 

  41. Ideker, T., Thorsson, V., Siegel, A.F., et al., J. Comput. Biol., 2000, vol. 7, p. 805.

    Article  CAS  Google Scholar 

  42. Cui, X. and Churchill, G.A., Genome Biol., 2003, vol. 4, p. 210.

    Article  Google Scholar 

  43. Slonim, O.K., Nat. Genet., 2002, vol. 32, p. 502.

    Article  CAS  Google Scholar 

  44. Runion, R., Spravochnik po neparametricheskoi statistike (Handbook of Nonparametric Statistics), Moscow: Finansy i statistika, 1982.

    Google Scholar 

  45. Pan, W., Lin, J., and Le, C., Funct. Integr. Genom., 2003, vol. 3, p. 117.

    Article  CAS  Google Scholar 

  46. Pan, W., Bioinformatics, 2002, vol. 18, p. 546.

    Article  CAS  Google Scholar 

  47. Quackenbush, J., Nat. Genet., 2002, vol. 32, p. 496.

    Article  CAS  Google Scholar 

  48. Thomas, J.G., Olson, J.M., Tapscott, S.J., et al., Genome Res., 2001, vol. 11, p. 1227.

    Article  CAS  Google Scholar 

  49. Tanaka, T.S., Jaradat, S.A., Lim, M.K., et al., Proc. Natl. Acad. Sci. USA, 2000, vol. 97, p. 9127.

    Article  Google Scholar 

  50. Baldi, P. and Long, A.D., Bioinformatics, 2001, vol. 17, p. 509.

    Article  CAS  Google Scholar 

  51. Lonnstedt, I. and Speed, T.P., Statistica Sinica, 2002, vol. 12, p. 31.

    Google Scholar 

  52. Storey, J.D., J. Royal Stat. Soc. Ser. B, 2002, vol. 64, p. 479.

    Article  Google Scholar 

  53. Benjamini, Y. and Hochberg, Y., Ibid., 1995, vol. 57, p. 289.

    Google Scholar 

  54. Storey, J. and Tibshirani, R., Proc. Natl. Acad. Sci. USA, 2003, vol. 100, p. 9440.

    Article  CAS  Google Scholar 

  55. Westfall, P.M. and Young, S.S., Resampling-Based Multiple Testing, New York: Wiley, 1993.

    Google Scholar 

  56. Kerr, M.K., Martin, M., and Churchill, G.A., J. Comput. Biol., 2000, vol. 7, p. 819.

    Article  CAS  Google Scholar 

  57. Pritchard, C.C., Hsu, L., Delrow, J., et al., Proc. Natl. Acad. Sci. USA, 2001, vol. 98, p. 13 266.

    Article  CAS  Google Scholar 

  58. DeJong, H., J. Comput. Biol., 2002, vol. 9, p. 67.

    Article  CAS  Google Scholar 

  59. Yeoh, E., Ross, M.E., Shurtleff, S.A., et al., Cancer Cell, 2002, vol. 1, p. 133.

    Article  CAS  Google Scholar 

  60. Stegmaier, K., Ross, K.N., Colavito, S.A., et al., Nat. Genet., 2004, vol. 36, p. 257.

    Article  CAS  Google Scholar 

  61. Jain, A.K. and Dubes, R.C., Algorithms for Clustering Data, Engle-wood Cliffs: Prentice-Hall, 1988.

    Google Scholar 

  62. Shamir, R. and Sharon, R., in: Current Topics in Computational. Biology, Jiang, T., Smith, T., Xu, Y., and Zhang, M., Eds., Boston: MIT Press, 2002, p. 269.

    Google Scholar 

  63. Valafar, F., Ann. N.Y. Acad. Sci., 2002, vol. 980, p. 41.

    CAS  Google Scholar 

  64. Kaufman, L. and Rousseeuw, P.J., Fitting Groups in Data. An Introduction to Cluster Analysis, New York: Wiley, 1990.

    Google Scholar 

  65. Eisen, M.B., Spellman, P.T., Brown, P.O., et al., Proc. Natl. Acad. Sci. USA, 1998, vol. 95, p. 14 863.

  66. Tamayo, P., Slonim, D., Mesirov, J., et al., Ibid., 1999, vol. 96, p. 2907.

    Article  CAS  Google Scholar 

  67. Tavazoie, S., Hughes, J.D., Cambell, M.J., et al., Nat. Genet., 1999, vol. 22, p. 281.

    Article  CAS  Google Scholar 

  68. Kohonen, T., Self-Organizing Maps, Berlin: Springer, 1997.

    Google Scholar 

  69. Yeung, K.Y., Fraley, C., Murua, A., et al., Bioinformatics, 2001, vol. 17, p. 977.

    Article  CAS  Google Scholar 

  70. Ghosh, D., Ibid., 2001, vol. 17, p. 275.

    Google Scholar 

  71. Fraley, C. and Raftery, A.E., The Computer J., 1998, vol. 41, p. 578.

    Article  Google Scholar 

  72. Hartuv, E., Schmitt, A., Lange, J., et al., In RECOMB99: Proceedings of the Third Annual International Conference on Computational Molecular Biology (RECOMB’99), Lyon: France, 1999, p. 188.

    Book  Google Scholar 

  73. Sharon, R., Maron-Katz, A., and Shamir, R., Bioinformatics, 2003, vol. 19, p. 1787.

    Article  CAS  Google Scholar 

  74. Dunn, J.C., J. Cybern., 1974, vol. 4, p. 95.

    Google Scholar 

  75. Halkidi, M., Batistakis, Y., and Vazirgiannis, M., Intel. Inform. Syst., 2001, vol. 17, p. 107.

    Article  Google Scholar 

  76. Getz, G., Levine, E., and Domany, E., Proc. Natl. Acad. Sci. USA, 2000, vol. 97, p. 12 079.

    Article  CAS  Google Scholar 

  77. Tibshirani, R., Hastie, T., Narasinmhan, B., et al., Ibid., 2002, vol. 99, p. 6567.

    Article  CAS  Google Scholar 

  78. Butte, A.J. and Hohane, I.S., Pac. Symp. Biocomp., 2000, p. 418.

  79. Datta, S., et al., Bioinformatics, 2003, vol. 19, p. 459.

    Article  CAS  Google Scholar 

  80. Banfleld, J. and Raftery, A.E., Biometrics, 1993, vol. 49, p. 803.

    Article  Google Scholar 

  81. Kass, R.E. and Raftery, A.E., J Am. Stat. Assoc., 1995, vol. 90, p. 773

    Article  Google Scholar 

  82. Tibshirani, R., Walther, G., and Hastie, T., J. Royal Stat. Soc. B, 2001, vol. 63, p. 411.

    Article  Google Scholar 

  83. Lange, T., Roth, V., Braun, M.L., et al., Neural Comput., 2004, vol. 16, p. 1299.

    Article  Google Scholar 

  84. Milligan, G.W. and Cooper, M.C., Psychometrika, 1985, vol. 50, p. 159.

    Article  Google Scholar 

  85. Dudoit, S. and Fridlyand, J., Genome Biol., 2002, vol. 3, p. 0036.1.

    Article  Google Scholar 

  86. Calinski, R. and Harabasz, J., Commun. Stat., 1974, vol. 3, p. 1.

    Article  Google Scholar 

  87. Krzanowski, W. and Lai, Y., Biometrics, 1985, vol. 44, p. 23.

    Article  Google Scholar 

  88. Giurcăneanu, C.D. and Tăbuş, I., Eur. J. Appl. Signal Proc., 2004, vol. 1, p. 64.

    Article  Google Scholar 

  89. Ben-Hur, A., Elisseeff, A., and Guyon, I., Pac. Symp. Biocomput., 2002, p. 6.

  90. Monti, S., Tamayo, P., Mesirov, J., et al., Machine Learning, 2003, vol. 52, p. 91.

    Article  Google Scholar 

  91. Bittner, M., Meltzer, P., Khan, J., et al., Nature, 2000, vol. 406, p. 536.

    Article  CAS  Google Scholar 

  92. Smolkin, M. and Ghosh, D., BMC Bioinformatics, 2003, vol. 4, p. 36.

    Article  Google Scholar 

  93. Zhang, K. and Zhao, H., Funct. Integr. Genomics, 2000, vol. 1, p. 156.

    Article  CAS  Google Scholar 

  94. Bhattacharjee, A., Richards, W.G., Staunton, J., et al., Proc. Natl. Acad. Sci. USA, 2001, vol. 98, p. 13 790.

    Article  CAS  Google Scholar 

  95. Kerr, M.K. and Churchill, G.A., Ibid., 2001, vol. 98, p. 8961.

    Article  CAS  Google Scholar 

  96. Gorge, N.R., Page, G.P., Sprague, A.P., et al., BMC Bioinformatics, 2005, vol. 6, p. S10.

    Article  CAS  Google Scholar 

  97. McShane, L.M., Radmacher, M.D., Friedlin, B., et al., Bioinformatics, 2002, vol. 18, p. 1462.

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to P. S. Ivanov.

Additional information

Original Russian Text © A.N. Sveshnikova, P.S. Ivanov, 2007, published in Russkii Khimicheskii Zhurnal, 2007, Vol. 51, No. 1, pp. 127–135.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sveshnikova, A.N., Ivanov, P.S. Biotechnology. Gene expression and microchips: Problems of the quantitative analysis. Russ J Gen Chem 77, 2071–2081 (2007). https://doi.org/10.1134/S1070363207110369

Download citation

  • Received:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S1070363207110369

Keywords

Navigation