Proceedings of 2015 Photonics & Electromagnetics Research Symposium, Prague, July 6 - 9,Page(s)1353-1356
Abstract
The fractal systems are broadly found throughout the nature, generally in any
scale. For each dimension (1D, 2D . . . ) in any structures and in any mathematical algorithms
or in any object (sequence, line, square) its dimension can be calculated. These dimensions are
specific parameters for description of the DNA sequence characters ACGT strings. Generally a
first step consists in the converting of a one-dimensional sequence into the image. In the second
step, the method for calculating the dimensions for all scales is selected. For the calculations
of the above mentioned dimensions the Power Spectrum (PS) method has been proposed and
examined. The Power Spectrum method provides universal calculation of dimension and it allows
to obtain the resulting multifractal coefficient. The multifractal coefficient represents the means
rate of approximation to ideal power spectrum. It has to be emphasized that the multifractal
coefficient is independent of any scale to be chosen. Moreover, the multifractal coefficient serves
as an advanced parameter for mathematical description of analyzed specific sequence of the
deoxyribonucleic acid (DNA) or the whole genome. The conversion of the sequence into the
image as the first step of the pre-processing can be used also for the alternative imaging and
the description of sequence and it is possible to choose another method for the processing and
analyzing a fractal image (for example Box Counting method). In the paper, the method for
the processing of the DNA in the genome sequencing, the Power Spectrum method, will be
introduced. The results of the Power Spectrum methods will be presented also.
Citation
Pavel Fiala,
Eva Gescheidtova,
and
Martin Valla,
"Power Spectrum Method for the Processing of the DNA in the Genome Sequencing," Proceedings of 2015 Photonics & Electromagnetics Research Symposium, Prague, July 6 - 9,Page(s)1353-1356
References
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2. Berthelsen, C. L., "Fractal analysis of DNA sequence data," 160, The University of Utah, 1993. Google Scholar