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Application of Chaos Game in Tri-Nucleotide Representation for the Comparison of Coding Sequences of β-Globin Gene

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Industry Interactive Innovations in Science, Engineering and Technology

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 11))

Abstract

In this paper, we use 2D tri-nucleotide representation based on chaos game theory. We extend the representation from 2D to 3D by taking the third coordinate as the multiple of the first two ones. Complete coding sequences of β globin genes of 10 species are now compared using four types of descriptors—1. Mean of the components of the represented sequences, 2. Standard deviation of the components of the represented sequence, 3. Highest eigen value of M/M matrix and 4. Highest eigen value of J/J matrix. The results in the four cases are critically examined. It is found that the use of J/J matrix with highest eigen value as the descriptor is the best one among the others.

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References

  1. Hamori, E., Ruskin, J.: H curves, a novel method of representation of nucleotide series especially suited for long DNA sequences. J. Biol. Chem. 258, 1318–1327 (1983)

    Google Scholar 

  2. Guo, F.B., Ou, H.Y., Zhang, C.T.: ZCURVE: a new system for recognizing protein–coding genes in bacterial and archaeal genomes. Nucl. Acids. Res. 31, 1780–1789 (2003)

    Article  Google Scholar 

  3. Zhang, C.T., Zhang, R.: Analysis of distribution of bases in the coding sequences by a diagrammatic technique. Nucl. Acids Res. 19, 6313–6317 (1991)

    Article  Google Scholar 

  4. Zhang, R., Zhang, C.T.: Z curves, an intuitive tool for visualizing and analyzing the DNA sequences. J. Biomol. Struct. Dyn. 11, 767–782 (1994)

    Article  Google Scholar 

  5. Nandy, A.: A new graphical representation and analysis of DNA sequence structure: I. Methodology and application to globin genes. Curr. Sci. 66, 309–314 (1994)

    Google Scholar 

  6. Randic, M., Vracko, M., Lers, N., Plavsic, D.: Novel 2–D graphical representation of DNA sequences and their numerical characterization. Chem. Phys. Lett. 368, 1–6 (2003)

    Article  Google Scholar 

  7. Randic, M., Vracko, M., Zupan, J., Novic, M.: Compact 2–D graphical representation of DNA. Chem. Phys. Lett. 373, 558–562 (2003)

    Article  Google Scholar 

  8. Liao, B., Wang, T.M.: Analysis of similarity/dissimilarity of DNA sequences based on 3–D graphical representation. Chem. Phys. Lett. 388, 195–200 (2004)

    Article  Google Scholar 

  9. Randic, M.: Graphical representations of DNA as 2–D map. Chem. Phys. Lett. 386, 468–471 (2004)

    Article  Google Scholar 

  10. Liao, B., Wang, T.M.: 3–D graphical representation of DNA sequences and their numerical characterization. J. Mol. Struct. (Theochem) 681, 209–212 (2004)

    Article  Google Scholar 

  11. Chi, R., Ding, K.Q.: Novel 4D numerical representation of DNA sequences. Chem. Phys. Lett. 407, 63–67 (2005)

    Article  Google Scholar 

  12. Yao, Y.H., Nan, X.Y., Wang, T.M.: A new 2D graphical representation—Classification curve and the analysis of similarity/dissimilarity of DNA sequences. J. Mol. Struct. (Theochem) 764, 101–108 (2006)

    Article  Google Scholar 

  13. Liao, B., Ding, K.Q.: A 3D graphical representation of DNA sequences and its application. Theor. Comput. Sci. 358, 56–64 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  14. Song, J., Tang, H.W.: A new 2–D graphical representation of DNA sequences and their numerical characterization. J. Biochem. Biophys. Methods 63, 228–239 (2005)

    Article  Google Scholar 

  15. Zhang, Z.J.: DV–Curve: a novel intuitive tool for visualizing and analyzing DNA sequences. Bioinformatics, vol. 25, pp. 1112–1117 (2009)

    Google Scholar 

  16. Yu, J., Wang, J., Sun, X.: Analysis of similarities/dissimilarities of DNA sequences based on a novel graphical representation. MATCH Commun. Math. Comput. Chem. 63, 493-512 (2010)

    Google Scholar 

  17. Das, S., Palit, S., Mahalanabish, A.R., Choudhury, N.R.: A new way to find similarity/dissimilarity of DNA sequences on the basis of dinucleotides representation. In: Computational Advancement in Communication Circuits and System, pp. 151–160. Springer (2015)

    Google Scholar 

  18. Randic, M., Zupan, J., Balaban, A.T.: Unique graphical representation of protein sequences based on nucleotide triplet codons. Chem. Phys. Lett. 397, 247–252 (2004)

    Article  Google Scholar 

  19. Luo, J., Guo, J., Li, Y.: A new graphical representation and its application in similarity/dissimilarity analysis of DNA sequences. In: 4th International Conference on Bioinformatics and Biomedical Engineering (2010). doi:10.1109/ICBBE.2010.5515203

  20. Kumar, S., Nei, M., Dudley, J., Tamura, K.: MEGA: a biologist-centric software for evolutionary analysis of DNA and protein sequences. Brief. Bioinform. 9, 299–306 (2008)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Computer Science & Engineering, Narula Institute of Technology, Kolkata, India

    Subhram Das & Nobhonil Roy Choudhury

  2. Bio-Science & Engineering, Jadavpur University, Kolkata, India

    D. N. Tibarewala & D. K. Bhattacharya

Authors
  1. Subhram Das
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  2. Nobhonil Roy Choudhury
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  3. D. N. Tibarewala
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  4. D. K. Bhattacharya
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Corresponding author

Correspondence to Subhram Das .

Editor information

Editors and Affiliations

  1. Department of Electronics and Communication, JIS College of Engineering (JISCE), Kalyani, West Bengal, India

    Swapan Bhattacharyya

  2. Department of Physics and Nanoscience and Technology, JIS College of Engineering (JISCE), Kalyani, West Bengal, India

    Sabyasachi Sen

  3. Department of Biomedical Engineering, JIS College of Engineering (JISCE), Kalyani, West Bengal, India

    Meghamala Dutta

  4. Department of Electrical Engineering, JIS College of Engineering (JISCE), Kalyani, West Bengal, India

    Papun Biswas

  5. Department of Mechanical Engineering, Jadavpur University, Kolkata, West Bengal, India

    Himadri Chattopadhyay

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Das, S., Choudhury, N.R., Tibarewala, D.N., Bhattacharya, D.K. (2018). Application of Chaos Game in Tri-Nucleotide Representation for the Comparison of Coding Sequences of β-Globin Gene. In: Bhattacharyya, S., Sen, S., Dutta, M., Biswas, P., Chattopadhyay, H. (eds) Industry Interactive Innovations in Science, Engineering and Technology . Lecture Notes in Networks and Systems, vol 11. Springer, Singapore. https://doi.org/10.1007/978-981-10-3953-9_54

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  • DOI: https://doi.org/10.1007/978-981-10-3953-9_54

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3952-2

  • Online ISBN: 978-981-10-3953-9

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