CFP last date
20 January 2025
Reseach Article

Biological Sequence Matching using Boolean algebra vs. Fuzzy Logic

by Nivit Gill, Shailendra Singh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 26 - Number 11
Year of Publication: 2011
Authors: Nivit Gill, Shailendra Singh
10.5120/3168-4383

Nivit Gill, Shailendra Singh . Biological Sequence Matching using Boolean algebra vs. Fuzzy Logic. International Journal of Computer Applications. 26, 11 ( July 2011), 15-21. DOI=10.5120/3168-4383

@article{ 10.5120/3168-4383,
author = { Nivit Gill, Shailendra Singh },
title = { Biological Sequence Matching using Boolean algebra vs. Fuzzy Logic },
journal = { International Journal of Computer Applications },
issue_date = { July 2011 },
volume = { 26 },
number = { 11 },
month = { July },
year = { 2011 },
issn = { 0975-8887 },
pages = { 15-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume26/number11/3168-4383/ },
doi = { 10.5120/3168-4383 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:12:31.998470+05:30
%A Nivit Gill
%A Shailendra Singh
%T Biological Sequence Matching using Boolean algebra vs. Fuzzy Logic
%J International Journal of Computer Applications
%@ 0975-8887
%V 26
%N 11
%P 15-21
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Biological sequence alignment is one of the crucial tasks of computational bioinformatics, and provides base for other tasks of bioinformatics. In this paper, we discuss two different approaches to sequence matching – Boolean algebra and fuzzy logic. First method is a two-valued logic whereas the second is a multi-valued logic. Both the methods perform sequence matching by direct comparison method using the operations of Boolean algebra and fuzzy logic respectively. To ensure the optimal alignment, dynamic programming is employed to align the sequences progressively. Both the methods are implemented and then tested on few sets of real biological sequences taken from NCBI bank and their performances are compared with the CLUSTALW algorithm.

References
  1. S. B. Needleman and C. D. Wunsch, "A general method applicable to the search for similarities in the amino acid sequence of two proteins," J. Molecular Biology, vol. 48, pp. 443-453, 1970.
  2. T. F. Smith and M. S. Waterman, "Identification of common molecular subsequence," J. Molecular Biology, vol. 147, pp. 195-197, 1981.
  3. L. Cai, D. Juedes, E. Liakhovitch, “Evolutionary computation techniques for multiple sequence alignment”, Proceedings of the 2000 Congress on Evolutionary Computation, 2000, pp. 829-835
  4. Swagatam Das & Debangshu Dey, “A new algorithm for local alignment in DNA sequencing”, Proc. of IEEE Conference, INDICON 2004, pp. 410-413.
  5. Bandyopadhyay, S.S.; Paul, S.; Konar, A., “Improved Algorithms for DNA Sequence Alignment and Revision of Scoring Matrix”, Proceedings of International Conference on Intelligent Sensing and Information Processing, 2005, pp. 485-490
  6. Pin-Teng Chang, Lung-Ting Hung, Kuo-Ping Lin, Chih-sheng Lin, Kuo-Chen Hung, “Protein Sequence Alignment Based on Fuzzy Arithmetic and Genetic Algorithm”, 2006 IEEE International Conference on Fuzzy Systems, pp. 1362-1367
  7. Y. Pan, Y. Chen, Juan Chen, Wei Liu, Ling Chen “Partitioned optimization algorithms for multiple sequence alignment”, Proceedings of the 20th International Conference on Advanced Information Networking and Applications, 2006, pp. 5
  8. Sara Nasser, Gregory L. Vert, Monica Nicolescu1 and Alison Murray, “Multiple Sequence Alignment using Fuzzy Logic”, Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, pp. 304-311
  9. Feng Yue and Jijun Tang, “A Divide-and-Conquer Implementation of Three Sequence Alignment and Ancestor Inference”, 2007 IEEE International Conference on Bioinformatics and Biomedicine, pp. 143-150
  10. Farhana Naznin, Ruhul Sarker, and Daryl Essam , “Iterative Progressive Alignment Method (IPAM) for Multiple Sequence Alignment”, Computers & Industrial Engineering, 2009. pp. 536-541
  11. V. Anitha and B. Poorna, “DNA Sequence Matching using Boolean Algebra”, 2010 International Conference on Advances in Computer Engineering, pp. 212-216.
  12. David W. Mount, “Bioinformatics: Sequence and Genome Analysis”, Cold Spring Harbor Laboratory Press
  13. E. Cox, “Fuzzy Fundamentals”, IEEE Spectrum October 1992, Volume 29, Issue 10, pp 58-61.
  14. “A Short tutorial on Fuzzy Logic”, http://www.cs.bilkent.edu.tr/~bulbul/depth/fuzzy.pdf
  15. Wikipedia Website, “Boolean Algebra”, http://en.wikipedia.org/wiki/Boolean_algebra_(logic).
  16. Wikipedia Website, “XNOR gate”, http://en.wikipedia.org/wiki/XNOR_gate.
  17. Wikipedia Website, “Needleman-Wunsch Algorithm”, http://en.wikipedia.org/wiki/Needleman-Wunsch_ algorithm.
  18. Wikipedia Website, “Fuzzy Logic”, http://en.wikipedia.org/wiki/Fuzzy_logic.
  19. Mathworks Website, “Fuzzy Logic Toolbox”, http://www.mathworks.com/help/toolbox/fuzzy.
  20. NCBI Website, “Influenza Virus Data base”, http://www.ncbi.nlm.nih.gov/genomes/FLU/Database/nph-select.cgi.
  21. GenomeNet Tools Website, “CLUSTALW TOOL”, http://www.genome.jp/tools/clustalw.
Index Terms

Computer Science
Information Sciences

Keywords

Sequence alignment Boolean algebra Fuzzy Logic Sequence matching global alignment dynamic programming