NDLI: Non-Stationary Analysis of DNA Sequences

Content Provider	IEEE Xplore Digital Library
Author	Bouaynaya, Nidhal Schonfeld, Dan
Copyright Year	2007
Description	Author affiliation: Department of Systems Engineering, University of Arkansas at Little Rock. (Bouaynaya, Nidhal) \|\| University of Illinois at Chicago, Dept. of Electrical and Computer Engineering (Schonfeld, Dan)
Abstract	Previous searches for long-range correlations in DNA sequences was carried out using statistical tools for stationary signals. However, genomic signals are non-stationary as can be attested by standard statistical tests for stationarity. In this paper, we address, in the light of non-stationary time-series analysis, the questions of (i) the existence of long-range correlations in DNA sequences and (ii) whether they are present in both coding and non-coding segments or only in the latter. It turns out that the statistical differences between coding and non-coding segments are more subtle than previously claimed by the stationary analysis. Both coding and non-coding sequences exhibit long-range correlations, as asserted by an evolutionary 1/f spectrum (i.e., having a time-dependent spectral exponent). Moreover, the average spectral exponent of non-coding segments is higher than its counterpart for coding segments. To prove that this observation is not an artifact of the 1/f evolutionary spectrum, we show, using an index of randomness that we derive from the frequency-time distribution of the genomic signals, that coding sequences are "more random" (i.e., whiter) than non-coding sequences. We believe that this result is likely the source of confusion and controversy in previous work, which relied on stationary analysis of DNA correlations.
Starting Page	200
Ending Page	204
File Size	3167151
Page Count	5
File Format	PDF
ISBN	9781424411979
DOI	10.1109/SSP.2007.4301247
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-08-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	DNA Sequences Genomics Bioinformatics Alzheimer's disease Testing White noise Signal analysis Time series analysis Autocorrelation empirical mode decomposition (EMD) Non-stationary time-series analysis evolutionary spectrum evolutionary periodogram Hilbert transform
Content Type	Text
Resource Type	Article

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