title: Insight into DNA periodicity by a single-channel sequence data approach.
abstract: It has not been obvious how to map a genomic sequence into the numbers to elucidate its periodicities by digital signal processing (DSP) in accord with the underlying biology [1]. The well known DNA spectra and their extensions appear the A-T-C-G--base-wise by Fourier (FT), wavelet (WT) or related transforms of the indicatory functions (IF-s) of these bases. The IF assumes either 1-in the presence or 0-in the absence of the indicated base in sequence. The IF's spectra can be next combined in a different way including the optimal one to provide the net spectrum [2]. In this contribution, it is attempted, and not limited to; showing that single channel numeric DNA also turns out to be sufficient for biologically meaningful results by DSP with accompanying merits. Plausibility is possible considering any RNA message as a single-channel coded waveform; by the triplets of the codon bases which code for 20 different amino acids. This in turn enables a clear justification for the coding rhythm in terms of the codon usage frequency (CUF) and the gene series autocorrelation. The latter simply assesses a self-similarity of the message. Along with appending well established communication insight to biological perspectives, the answer to how the genetic code is becoming specific, inducing the self-similarity of the coded sequences under the three-base-shift case is addressed. Supporting the focus, there are some findings in vertebrates' genes data elucidated by the EMD of Huang-Hilbert transform (H-HT) [3]; these are long-term spectra relevant to the coding, the content of dicodons and the structural properties of coded proteins [4]. Also a new finding in the coding rhythm--the one which is attributed to the coding DNA, is included. This is the net coding rhythms in Homo sapiens, Homo sapiens house-keeping and vertebrates' genes comparison by histograms of adaptively tracked amplitudes case. It is intriguing how spectral features of genomic sequences correspond to related physical phenomena [5-8].
authors.affiliation: CM UMK, Bydgoszcz, Poland. mzoltowski@cm.umk.pl
authors.forename: Mariusz
authors.initials: M
authors.lastname: Zoltowski
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D004247:DNA / Q000737:chemistry* / Q000235:genetics*; D008969:Molecular Sequence Data; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012815:Signal Processing, Computer-Assisted
chemical_list: D004247:DNA