Skip to main content
Log in

In search of coding and non-coding regions of DNA sequences based on balanced estimation of diffusion entropy

  • Original Paper
  • Published:
Journal of Biological Physics Aims and scope Submit manuscript

Abstract

Identification of coding regions in DNA sequences remains challenging. Various methods have been proposed, but these are limited by species-dependence and the need for adequate training sets. The elements in DNA coding regions are known to be distributed in a quasi-random way, while those in non-coding regions have typical similar structures. For short sequences, these statistical characteristics cannot be extracted correctly and cannot even be detected. This paper introduces a new way to solve the problem: balanced estimation of diffusion entropy (BEDE).

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.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Kotlar, D., Lavner, T.: Gene prediction by spectral rotation measure: a new method for identifying protein-coding regions. Genome Res. 13(18), 1930–1937 (2003)

    Google Scholar 

  2. Lobzin, V.V., Chechetkin, V.R.: Order and correlations in genomic DNA sequences. The spectral approach. Physics-Uspekhi 43, 55–78 (2000)

    Article  ADS  Google Scholar 

  3. Anastassiou, D.: Frequency-domain analysis of biomolecular sequences. Bioinformatics 16(12), 1073–1081 (2000)

    Article  MathSciNet  Google Scholar 

  4. Grosse, I., Herzel, H., Buldyrev, S.V., Stanley, H.E.: Species independence of mutual information in coding and noncoding DNA. Phys. Rev. E 61(5), 5624–5629 (2000)

    Article  ADS  Google Scholar 

  5. Bernaola-Galván, P., Grosse, I., Carpena, P., Oliver, J.L., Román-Roldán, R., Stanley, H.E.: Finding borders between coding and noncoding DNA regions by an entropic segmentation method. Phys. Rev. Lett. 85(6), 1342–1345 (2000)

    Article  ADS  Google Scholar 

  6. Barral, J.P., Hasmy, A., Jiménez, J., Marcano, A.: Nonlinear modeling technique for the analysis of DNA chains. Phys. Rev. E 61(2), 1812–1815 (2000)

    Article  ADS  Google Scholar 

  7. Scafetta, N., Hamilton, P., Grigolini, P.: The thermodynamics of social processes: the teen birth phenomenon. Fractals 9(2), 193–208 (2001)

    Article  Google Scholar 

  8. Grigolini, P., Leddon, D., Scafetta, N.: Diffusion entropy and waiting time statistics of hard-x-ray solar flares. Phys. Rev. E 65(4), 046203 (2002)

    Article  ADS  Google Scholar 

  9. Yang, H.J., Zhao, F.C., Qi, L.Y., Hu, B.L.: Temporal series analysis approach to spectra of complex networks. Phys. Rev. E 69(6), 066104 (2004)

    Article  ADS  Google Scholar 

  10. Yang, H.J., Zhao, F.C., Zhang, W., Li, Z.N.: Diffusion entropy approach to complexity for a Hodgkin–Huxley neuron. Physica A 347, 704–710 (2005)

    Article  ADS  Google Scholar 

  11. Cai, S.M., Zhou, P.L., Yang, H.J., Yang, C.X., Wang, B.H., Zhou, T.: Diffusion entropy analysis on the scaling behavior of financial markets. Physica A 367, 337–344 (2006)

    Article  ADS  Google Scholar 

  12. Scafetta, N., Latora, V., Grigolini, P.: Lévy scaling: the diffusion entropy analysis applied to DNA sequences. Phys. Rev. E 66(3), 031906 (2002)

    Article  MathSciNet  ADS  Google Scholar 

  13. Allegrini, P., Bellazzini, J., Bramanti, G., et al.: Scaling breakdown: a signature of aging. Phys. Rev. E 66(1), 015101 (2002)

    Article  ADS  Google Scholar 

  14. Qi, J.C., Yang, H.J.: Hurst exponents for short time series. Phys. Rev. E 84(6), 066114 (2011)

    Article  ADS  Google Scholar 

  15. Zhang, W., Qiu, L., Xiao, Q., Yang, H.J., Zhang, Q., Wang, J.: Evaluation of scale invariance in physiological signals by means of balanced estimation of diffusion entropy. Phys. Rev. E 86(5), 056107 (2012)

    Article  ADS  Google Scholar 

  16. Stanley, H.E., Buldyrev, S.V., Goldberger, A.L., Havlin, S., Peng, C.K., Simons, M.: Scaling features of noncoding DNA. Physica A 273(1–2), 1–18 (1999)

    Article  ADS  Google Scholar 

  17. Yang, H.J., Zhao, F.C., Zhuo, Y.Z., Wu X.Z.: Analysis of DNA chains by means of factorial moments. Phys. Lett. A 292(6), 349–356 (2002)

    Article  ADS  MATH  Google Scholar 

  18. García, P., Jiménez, J., Marcano, A., Molelro, F.: Local optimal metrics and nonlinear modeling of chaotic time series. Phys. Rev. Lett. 76(9), 1449–1452 (1996)

    Article  ADS  Google Scholar 

Download references

Conflict of interest

The authors declare no conflict of interest.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jin Zhang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, J., Zhang, W. & Yang, H. In search of coding and non-coding regions of DNA sequences based on balanced estimation of diffusion entropy. J Biol Phys 42, 99–106 (2016). https://doi.org/10.1007/s10867-015-9399-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10867-015-9399-7

Keywords

Navigation