Literature DB >> 18029086

Discriminating coding, non-coding and regulatory regions using rescaled range and detrended fluctuation analysis.

Rene Te Boekhorst1, Irina Abnizova, Chrystopher Nehaniv.   

Abstract

In this paper we analyse the efficiency of two methods, rescaled range analysis and detrended fluctuation analysis, in distinguishing between coding DNA, regulatory DNA and non-coding non-regulatory DNA of Drosophila melanogaster. Both methods were used to estimate the degree of sequential dependence (or persistence) among nucleotides. We found that these three types of DNA can be discriminated by both methods, although rescaled range analysis performs slightly better than detrended fluctuation analysis. On average, non-coding, non-regulatory DNA has the highest degree of sequential persistence. Coding DNA could be characterised as being anti-persistent, which is in line with earlier findings of latent periodicity. Regulatory regions are shown to possess intermediate sequential dependency. Together with other available methods, rescaled range and detrended fluctuation analysis on the basis of a combined purine/pyrimidine and weak/strong classification of the nucleotides are useful tools for refined structural and functional segmentation of DNA.

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Year:  2007        PMID: 18029086     DOI: 10.1016/j.biosystems.2007.05.019

Source DB:  PubMed          Journal:  Biosystems        ISSN: 0303-2647            Impact factor:   1.973


  3 in total

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Authors:  Bo Chen; Ping Ji
Journal:  Nucleic Acids Res       Date:  2010-10-14       Impact factor: 16.971

2.  Characterizing exons and introns by regularity of nucleotide strings.

Authors:  Tonya Woods; Thanawadee Preeprem; Kichun Lee; Woojin Chang; Brani Vidakovic
Journal:  Biol Direct       Date:  2016-02-08       Impact factor: 4.540

3.  Detecting the borders between coding and non-coding DNA regions in prokaryotes based on recursive segmentation and nucleotide doublets statistics.

Authors:  Suping Deng; Yixiang Shi; Liyun Yuan; Yixue Li; Guohui Ding
Journal:  BMC Genomics       Date:  2012-12-17       Impact factor: 3.969

  3 in total

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