Skip to main content

On prokaryotes’ clustering based on curvature distribution

  • Chapter
  • 659 Accesses

Part of the book series: Studies in Computational Intelligence ((SCI,volume 23))

1 Abstract

Massive determination of complete genomes sequences has led to development of different tools for genome comparisons. Our approach is to compare genomes according to typical genomic distributions of a mathematical function that reflects a certain biological function. In this study we used comprehensive genome analysis of DNA curvature distributions before starts and after ends of prokaryotic genes to evaluate the assistance of mathematical and statistical procedures. Due to an extensive amount of data we were able to define the factors influencing the curvature distribution in promoter and terminator regions. Two clustering methods, K-means and PAM were applied and produced very similar clusterings that reflect genomic attributes and environmental conditions of species’ habitat.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
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

  1. S. Andersson, A. Zomorodipour, J. Andersson, T. Sicheritz-Pontent, U. Alsmark, R. Podowski, A. Naslund, A. Eriksson, H. Winkler, and C. Kurland. The genome sequence of Rickettsia prowazekii and the origin of mitochondria. Nature, 396:109–110, 1998.

    Article  Google Scholar 

  2. A Bolshoy, P. McNamara, R.E. Harrington, and E.N. Trifonov. Curved DNA without A-A: experimental estimation of all 16 DNA wedge angles. Proc Natl Acad. Sci. U.S.A., 88:2312–2316, 1991.

    Article  Google Scholar 

  3. S. Diekmann and J.C. Wang. On the sequence determinants and flexibility of the kinetoplast DNA fragment with abnormal gel electrophoretic mobilities. J. Mol. Biol., 186:1–11, 1985.

    Article  Google Scholar 

  4. E. Forgy. Cluster analysis of multivariate data: Efficiency vs. interpretability of classifications. Biometrics, 21(3):768, 1965.

    Google Scholar 

  5. C. Fraley and A.E. Raftery. How many clusters? Which clustering method? Answers via model-based cluster analysis. The Computer Journal, 41(8):578–588, 1998.

    Article  MATH  Google Scholar 

  6. C. Fraser, J. Gocanye, O. White, M. Adams, R. Clayton, R. Fleischmann, D. Bult, A. Kerlavage, G. Sutton, J. Kelly, and et al. The minimal gene complement of Mycoplasma genitalium. Science, 270:397–403, 1995.

    Google Scholar 

  7. J. Griffith, M. Bleyman, C.A. Rauch, P.A. Kitchin, and P.T. Englund. Visualization of the bent helix in kinetoplast DNA by electron microscopy. Cell, 46:717–724, 1986.

    Article  Google Scholar 

  8. S. Hosid and A. Bolshoy. New elements of the termination of transcription in prokaryotes. J. Biomol. Struct. Dyn., 22:347–354, 2004.

    Google Scholar 

  9. W. Kabsch, C. Sander, and E.N. Trifonov. The ten helical twist angles of BDNA. Nucleic Acids Res., 10(3):1097–1104, 1982.

    Google Scholar 

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

    Google Scholar 

  11. L. Kozobay-Avraham, S. Hosid, and A. Bolshoy. Curvature distribution in prokaryotic genomes. In Silico Biol., 4(3):361–375, 2004.

    Google Scholar 

  12. L. Kozobay-Avraham, S. Hosid, and A. Bolshoy. Involvement of DNA curvature in intergenic regions of prokaryotes. Nucleic Acids Res., submited, 2006.

    Google Scholar 

  13. W. Krzanowski and Y. Lai. A criterion for determining the number of groups in a dataset using sum of squares clustering. Biometrics, 44:23–34, 1985.

    Article  MathSciNet  Google Scholar 

  14. J. Mardia, K. Kent and J. Bibby. Multivariate Analysis. Academic Press, San Diego, 1979.

    MATH  Google Scholar 

  15. J.C. Marini, S.D. Levene, D.M. Crothers, and P.T. Englund. Bent helical structure in kinetoplast DNA. Proc. Natl. Acad. Sci. U.S.A., 79:7664–7668, 1982.

    Article  Google Scholar 

  16. J. Perez-Martin, F. Rojo, and de V. Lorenzo. Promoters responsive to DNA bending: a common theme in prokaryotic gene expression. Microbiol. Rev., 58:268–290, 1994.

    Google Scholar 

  17. S. Shigenobu, H. Watanabe, M. Hattori, K. Sakaki, and H. Ishikawa. Genome sequence of the endocellular bacterial symbiont of aphids Buchnera sp. aps. Nature, 7:81–86, 2000.

    Google Scholar 

  18. E.S. Shpigelman, E.N. Trifonov, and A. Bolshoy. Curvature: software for the analysis of curved DNA. Comput. Appl. Biosci., 9:435–440, 1993.

    Google Scholar 

  19. C. Sugar and G. James. Finding the number of clusters in a data set: An information theoretic approach. J of the American Statistical Association, 98:750–763, 2003.

    Article  MATH  MathSciNet  Google Scholar 

  20. E. N. Trifonov and L. E. Ulanovsky. Inherently curved DNA and its structural elements. In Unusual DNA Structures, Wells, R. D. and Harvey, S. C. (eds.), pages 173–187. Springer-Verlag, Berlin, 1987.

    Google Scholar 

  21. E.N. Trifonov. Curved DNA. CRC Crit Rev Biochem, 19:89–106, 1985.

    Google Scholar 

  22. H.M. Wu and D.M. Crothers. The locus of sequence-directed and protein-induced DNA bending. Nature, 308:509–513, 1984.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Kozobay-Avraham, L., Bolshoy, A., Volkovich, Z. (2006). On prokaryotes’ clustering based on curvature distribution. In: Last, M., Szczepaniak, P.S., Volkovich, Z., Kandel, A. (eds) Advances in Web Intelligence and Data Mining. Studies in Computational Intelligence, vol 23. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-33880-2_28

Download citation

  • DOI: https://doi.org/10.1007/3-540-33880-2_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33879-6

  • Online ISBN: 978-3-540-33880-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics