Phys. Rev. E 58, 3578 - 3584 (1998)

Characterizing self-similarity in bacteria DNA sequences

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Xin Lu1 *, Zhirong Sun2, Huimin Chen1, and Yanda Li1
1Department of Automation, Tsinghua University, 100084 Beijing, People’s Republic of China
2Department of Biology, Tsinghua University, 100084 Beijing, People’s Republic of China

Received 24 November 1997; revised 27 April 1998

In this paper some parametric methods are introduced to characterize the self-similarity of DNA sequences. Compared with Fourier analysis, these methods perform statistically more stably and yield more reliable results. Using these methods, eight whole genomes of bacteria provided by NCBI are analyzed. Long-range correlation properties in the nucleotide density distribution along these DNA sequences are explored. Estimation results show that the long-range correlation structure prevails through the entire molecule of DNA. Higher order statistics through coarse graining reveal that rather than multifractal, there are only monofractal phenomena presented in the sequences. Hence, the nucleotide density distribution can be modeled asymptotically as fractional Gaussian noise. This result points to a new direction for analyzing and understanding the intrinsic structures of DNA sequences.


©1998 The American Physical Society

URL: http://link.aps.org/abstract/PRE/v58/p3578
DOI: 10.1103/PhysRevE.58.3578
PACS: 87.10.+e

* Electronic address: luxin@jerry.au.tsinghua.edu.cn

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