Discriminant Analysis for the Eigenvalues of Variance Covariance Matrix of FFT Scaling of DNA Sequences: An Empirical Study of Some Organisms

Salah Hamza Abid; Jinan Hamza Farhood

doi:doi:10.11648/j.ijiis.20190801.15

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Discriminant Analysis for the Eigenvalues of Variance Covariance Matrix of FFT Scaling of DNA Sequences: An Empirical Study of Some Organisms

Salah Hamza Abid, Jinan Hamza Farhood

Published in International Journal of Intelligent Information Systems (Volume 8, Issue 1)

Received: 19 January 2019 Accepted: 11 March 2019 Published: 27 March 2019

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Abstract

Many studies discussed different numerical representations of DNA sequences. One naive approach for exploring the nature of a DNA sequence is to assign numerical values (or scales) to the nucleotides and then proceed with standard time series methods. The analysis will depend actually on the particular assignment of numerical values.Discriminant analysis aims to examine the dependence of one qualitative (classification) variable from several quantitative variables according to number of variations of qualitative variable we can distinction. Actually, there is a discriminant analysis for two or more groups. The essential work of discriminant analysis is to get the optimal assigning rules that will minimize the likelihood of incorrect classification of elements. In this paper, we discussed the discriminant analysis of the first, second, third and fourth eigenvalues of variance covariance matrix of Fast Fourier Transform (FFT) for numerical values representation of DNA sequences of five organisms, Human, E. coli, Rat, Wheat and Grasshopper. The analysis is based on three methods (All Variables, Forward Selection and Backward Selection) of discrimination. Functions have been reached whereby discrimination is made among organisms under consideration. Empirical studies are conducted to show the value of our point of view and the applications based on. Therefore, we recommended that, other empirical studies should be done for other organisms and statistical methods by using the point of view adopted here. Also, aspects stated here must be used in an applied manner for DNA sequences discrimination.

Published in	International Journal of Intelligent Information Systems (Volume 8, Issue 1)
DOI	10.11648/j.ijiis.20190801.15
Page(s)	26-42
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

FFT Scaling, DNA, Classification, Discriminant Analysis (DA), All Variables, Forward Selection, Backward Selection, Wilks-Lambda, Eigenvalue

References

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Salah Hamza Abid, Jinan Hamza Farhood. (2019). Discriminant Analysis for the Eigenvalues of Variance Covariance Matrix of FFT Scaling of DNA Sequences: An Empirical Study of Some Organisms. International Journal of Intelligent Information Systems, 8(1), 26-42. https://doi.org/10.11648/j.ijiis.20190801.15

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ACS Style

Salah Hamza Abid; Jinan Hamza Farhood. Discriminant Analysis for the Eigenvalues of Variance Covariance Matrix of FFT Scaling of DNA Sequences: An Empirical Study of Some Organisms. Int. J. Intell. Inf. Syst. 2019, 8(1), 26-42. doi: 10.11648/j.ijiis.20190801.15

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Salah Hamza Abid, Jinan Hamza Farhood. Discriminant Analysis for the Eigenvalues of Variance Covariance Matrix of FFT Scaling of DNA Sequences: An Empirical Study of Some Organisms. Int J Intell Inf Syst. 2019;8(1):26-42. doi: 10.11648/j.ijiis.20190801.15

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@article{10.11648/j.ijiis.20190801.15,
  author = {Salah Hamza Abid and Jinan Hamza Farhood},
  title = {Discriminant Analysis for the Eigenvalues of Variance Covariance Matrix of FFT Scaling of DNA Sequences: An Empirical Study of Some Organisms},
  journal = {International Journal of Intelligent Information Systems},
  volume = {8},
  number = {1},
  pages = {26-42},
  doi = {10.11648/j.ijiis.20190801.15},
  url = {https://doi.org/10.11648/j.ijiis.20190801.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijiis.20190801.15},
  abstract = {Many studies discussed different numerical representations of DNA sequences. One naive approach for exploring the nature of a DNA sequence is to assign numerical values (or scales) to the nucleotides and then proceed with standard time series methods. The analysis will depend actually on the particular assignment of numerical values.Discriminant analysis aims to examine the dependence of one qualitative (classification) variable from several quantitative variables according to number of variations of qualitative variable we can distinction. Actually, there is a discriminant analysis for two or more groups. The essential work of discriminant analysis is to get the optimal assigning rules that will minimize the likelihood of incorrect classification of elements. In this paper, we discussed the discriminant analysis of the first, second, third and fourth eigenvalues of variance covariance matrix of Fast Fourier Transform (FFT) for numerical values representation of DNA sequences of five organisms, Human, E. coli, Rat, Wheat and Grasshopper. The analysis is based on three methods (All Variables, Forward Selection and Backward Selection) of discrimination. Functions have been reached whereby discrimination is made among organisms under consideration. Empirical studies are conducted to show the value of our point of view and the applications based on. Therefore, we recommended that, other empirical studies should be done for other organisms and statistical methods by using the point of view adopted here. Also, aspects stated here must be used in an applied manner for DNA sequences discrimination.},
 year = {2019}
}

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TY - JOUR
T1 - Discriminant Analysis for the Eigenvalues of Variance Covariance Matrix of FFT Scaling of DNA Sequences: An Empirical Study of Some Organisms
AU - Salah Hamza Abid
AU - Jinan Hamza Farhood
Y1 - 2019/03/27
PY - 2019
N1 - https://doi.org/10.11648/j.ijiis.20190801.15
DO - 10.11648/j.ijiis.20190801.15
T2 - International Journal of Intelligent Information Systems
JF - International Journal of Intelligent Information Systems
JO - International Journal of Intelligent Information Systems
SP - 26
EP - 42
PB - Science Publishing Group
SN - 2328-7683
UR - https://doi.org/10.11648/j.ijiis.20190801.15
AB - Many studies discussed different numerical representations of DNA sequences. One naive approach for exploring the nature of a DNA sequence is to assign numerical values (or scales) to the nucleotides and then proceed with standard time series methods. The analysis will depend actually on the particular assignment of numerical values.Discriminant analysis aims to examine the dependence of one qualitative (classification) variable from several quantitative variables according to number of variations of qualitative variable we can distinction. Actually, there is a discriminant analysis for two or more groups. The essential work of discriminant analysis is to get the optimal assigning rules that will minimize the likelihood of incorrect classification of elements. In this paper, we discussed the discriminant analysis of the first, second, third and fourth eigenvalues of variance covariance matrix of Fast Fourier Transform (FFT) for numerical values representation of DNA sequences of five organisms, Human, E. coli, Rat, Wheat and Grasshopper. The analysis is based on three methods (All Variables, Forward Selection and Backward Selection) of discrimination. Functions have been reached whereby discrimination is made among organisms under consideration. Empirical studies are conducted to show the value of our point of view and the applications based on. Therefore, we recommended that, other empirical studies should be done for other organisms and statistical methods by using the point of view adopted here. Also, aspects stated here must be used in an applied manner for DNA sequences discrimination.
VL - 8
IS - 1
ER -

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Salah Hamza Abid

Mathematics Department, Education College, Al-Mustansiriya University, Baghdad, Iraq
Jinan Hamza Farhood

Mathematics Department, Education College, Babylon University, Babil, Iraq

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Salah Hamza Abid, Jinan Hamza Farhood. (2019). Discriminant Analysis for the Eigenvalues of Variance Covariance Matrix of FFT Scaling of DNA Sequences: An Empirical Study of Some Organisms. International Journal of Intelligent Information Systems, 8(1), 26-42. https://doi.org/10.11648/j.ijiis.20190801.15

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ACS Style

Salah Hamza Abid; Jinan Hamza Farhood. Discriminant Analysis for the Eigenvalues of Variance Covariance Matrix of FFT Scaling of DNA Sequences: An Empirical Study of Some Organisms. Int. J. Intell. Inf. Syst. 2019, 8(1), 26-42. doi: 10.11648/j.ijiis.20190801.15

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Salah Hamza Abid, Jinan Hamza Farhood. Discriminant Analysis for the Eigenvalues of Variance Covariance Matrix of FFT Scaling of DNA Sequences: An Empirical Study of Some Organisms. Int J Intell Inf Syst. 2019;8(1):26-42. doi: 10.11648/j.ijiis.20190801.15

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@article{10.11648/j.ijiis.20190801.15,
  author = {Salah Hamza Abid and Jinan Hamza Farhood},
  title = {Discriminant Analysis for the Eigenvalues of Variance Covariance Matrix of FFT Scaling of DNA Sequences: An Empirical Study of Some Organisms},
  journal = {International Journal of Intelligent Information Systems},
  volume = {8},
  number = {1},
  pages = {26-42},
  doi = {10.11648/j.ijiis.20190801.15},
  url = {https://doi.org/10.11648/j.ijiis.20190801.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijiis.20190801.15},
  abstract = {Many studies discussed different numerical representations of DNA sequences. One naive approach for exploring the nature of a DNA sequence is to assign numerical values (or scales) to the nucleotides and then proceed with standard time series methods. The analysis will depend actually on the particular assignment of numerical values.Discriminant analysis aims to examine the dependence of one qualitative (classification) variable from several quantitative variables according to number of variations of qualitative variable we can distinction. Actually, there is a discriminant analysis for two or more groups. The essential work of discriminant analysis is to get the optimal assigning rules that will minimize the likelihood of incorrect classification of elements. In this paper, we discussed the discriminant analysis of the first, second, third and fourth eigenvalues of variance covariance matrix of Fast Fourier Transform (FFT) for numerical values representation of DNA sequences of five organisms, Human, E. coli, Rat, Wheat and Grasshopper. The analysis is based on three methods (All Variables, Forward Selection and Backward Selection) of discrimination. Functions have been reached whereby discrimination is made among organisms under consideration. Empirical studies are conducted to show the value of our point of view and the applications based on. Therefore, we recommended that, other empirical studies should be done for other organisms and statistical methods by using the point of view adopted here. Also, aspects stated here must be used in an applied manner for DNA sequences discrimination.},
 year = {2019}
}

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