Spectrum and symbol distribution of nucleotide sequences

Afreixo, Vera; Ferreira, Paulo J. S. G.; Santos, Dorabella

doi:10.1103/physreve.70.031910

Cited by 14 publications

(7 citation statements)

References 11 publications

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“…Figure 7 reveals a local peak at k = N /3, which corresponds to a period of three samples. It is known that the symbolic autocorrelation spectrum of protein coding DNA regions typically has a peak at k = N /3 frequency (Afreixo et al , 2004b ; Voss, 1992 ; Wang and Johnson, 2002 ). It has been shown in Afreixo et al ( 2004a ) that the symbolic autocorrelation spectrum and the indicator sequences spectrum are equivalent concepts.…”

Section: Resultsmentioning

confidence: 99%

Genome analysis with inter-nucleotide distances

et al. 2009

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Motivation: DNA sequences can be represented by sequences of four symbols, but it is often useful to convert the symbols into real or complex numbers for further analysis. Several mapping schemes have been used in the past, but they seem unrelated to any intrinsic characteristic of DNA. The objective of this work was to find a mapping scheme directly related to DNA characteristics and that would be useful in discriminating between different species. Mathematical models to explore DNA correlation structures may contribute to a better knowledge of the DNA and to find a concise DNA description.Results: We developed a methodology to process DNA sequences based on inter-nucleotide distances. Our main contribution is a method to obtain genomic signatures for complete genomes, based on the inter-nucleotide distances, that are able to discriminate between different species. Using these signatures and hierarchical clustering, it is possible to build phylogenetic trees. Phylogenetic trees lead to genome differentiation and allow the inference of phylogenetic relations. The phylogenetic trees generated in this work display related species close to each other, suggesting that the inter-nucleotide distances are able to capture essential information about the genomes. To create the genomic signature, we construct a vector which describes the inter-nucleotide distance distribution of a complete genome and compare it with the reference distance distribution, which is the distribution of a sequence where the nucleotides are placed randomly and independently. It is the residual or relative error between the data and the reference distribution that is used to compare the DNA sequences of different organisms.Contact: vera@ua.pt

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Section: Resultsmentioning

confidence: 99%

Genome analysis with inter-nucleotide distances

et al. 2009

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“…Discrete Fourier Transform (DFT) is a powerful tool in signal and image processing. During recent years, DFT has been increasingly used in DNA research, such as gene prediction, protein coding region, genomic signature, hierarchical clustering, periodicity analysis (Tiwari et al, 1997;Anastassiou, 2000;Kotlar and Lavner, 2003;Vaidyanathan and Yoon, 2004;Afreixo et al, 2004Afreixo et al, , 2009Tenreiro Machado et al, 2011). A DFT power spectrum of a DNA sequence reflects the nucleotide distribution and periodic Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/yjtbi patterns of that sequence, and it has been applied to identify protein coding regions in genomic sequences (Fukushima et al, 2002;Yau, 2005, 2007).…”

Section: Introductionmentioning

confidence: 99%

A new method to cluster DNA sequences using Fourier power spectrum

Hoang

Yin

Zheng

et al. 2015

Journal of Theoretical Biology

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A novel clustering method is proposed to classify genes and genomes. For a given DNA sequence, a binary indicator sequence of each nucleotide is constructed, and Discrete Fourier Transform is applied on these four sequences to attain respective power spectra. Mathematical moments are built from these spectra, and multidimensional vectors of real numbers are constructed from these moments. Cluster analysis is then performed in order to determine the evolutionary relationship between DNA sequences. The novelty of this method is that sequences with different lengths can be compared easily via the use of power spectra and moments. Experimental results on various datasets show that the proposed method provides an efficient tool to classify genes and genomes. It not only gives comparable results but also is remarkably faster than other multiple sequence alignment and alignment-free methods.

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“…This paper studies the deoxyribonucleic acid (DNA) code [Afreixo et al, 2004a;Emanuele II et al, 2005;Jeng et al, 2006;Sims et al, 2009;Yin & Yau, 2005] from the perspective of frac-tional dynamics. It is believed that, for a given living being, besides information about its "struc-tural construction", DNA also includes other levels of information such as the history of its evolution up to the present state, or instructions for the behavior of each individual during its lifetime [Afreixo et al, 2004b;Dunn et al, 2008;Leit˜ao et al, 2005]. These distinct time scales reveal that we are in the presence of a complex code and that usual tools for the study of dynamical systems may be helpful in this endeavour.…”

Section: Introductionmentioning

confidence: 99%