CFP last date
22 April 2024
Reseach Article

TSGA-MSA: Trace Sequence Algorithm for Alignment of MSA

Published on April 2014 by Ruchi Gupta, Pankaj Agarwal, A.k Soni
International Conference on Advances in Computer Engineering and Applications
Foundation of Computer Science USA
ICACEA - Number 6
April 2014
Authors: Ruchi Gupta, Pankaj Agarwal, A.k Soni
39c702c8-0ba7-4faf-ab12-90c8c57df078

Ruchi Gupta, Pankaj Agarwal, A.k Soni . TSGA-MSA: Trace Sequence Algorithm for Alignment of MSA. International Conference on Advances in Computer Engineering and Applications. ICACEA, 6 (April 2014), 21-26.

@article{
author = { Ruchi Gupta, Pankaj Agarwal, A.k Soni },
title = { TSGA-MSA: Trace Sequence Algorithm for Alignment of MSA },
journal = { International Conference on Advances in Computer Engineering and Applications },
issue_date = { April 2014 },
volume = { ICACEA },
number = { 6 },
month = { April },
year = { 2014 },
issn = 0975-8887,
pages = { 21-26 },
numpages = 6,
url = { /proceedings/icacea/number6/15839-1473/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Advances in Computer Engineering and Applications
%A Ruchi Gupta
%A Pankaj Agarwal
%A A.k Soni
%T TSGA-MSA: Trace Sequence Algorithm for Alignment of MSA
%J International Conference on Advances in Computer Engineering and Applications
%@ 0975-8887
%V ICACEA
%N 6
%P 21-26
%D 2014
%I International Journal of Computer Applications
Abstract

Multiple sequence alignment (MSA) is an NP-complete and important problem in bioinformatics. In this paper, we have proposed iterative alignment method using a Genetic Algorithm for Multiple Sequence Alignment, named TSGA-MSA. The steps in this algorithm are discussed in details and its performances on a set of benchmark datasets from the BAliBase 2. 0 are analysed. The experimental results, the effects of the initial generation and genetic operators on the performance of this algorithm, the parameter settings, and a comparison of results with other well-known algorithm are presented and discussed.

References
  1. Notredame,C. : Recent progress in multiple sequence alignment: a survey, Pharmcogemmics, vol. 3, 2002, pp. 131-144.
  2. Notredame, C. and Higgins, D. G. : SAGA: Sequence alignment by genetic algorithm, Nucleic Acids Res. , vol. 24, 1996, pp. 1515–1524.
  3. Anabarasu, L. A. : Multiple sequence alignment using parallel genetic algorithms, In the Second Asia-Pacific Conference on Simulated Evolution (SEAL-98). Canberra Australia, 1998, pp. 201-210.
  4. Notredame, C. , Holm, L. and Higgins, D. G. : COFFEE: an objective function for multiple sequence alignments, Bioinformatics, vol. 14(5), 1998, pp. 407-422.
  5. Zhang, C. Wong AKC. : Toward efficient multiple molecular sequence alignment: a system of genetic algorithm and dynamic programming, IEEE Transactions on Systems, Man and Cybernetics, 1997, pp. 918 - 932.
  6. Cai, L. , Juedes, D. and Liakhovitch, E. : Evolutionary computation techniques for multiple sequence alignment. Congress on Evolutionary Computation (CEC 2000), 2000, pp. 829-835.
  7. Thomsen, R. , Fogel GB. and Krink ,T. : Improvement of clustal–derived sequence alignments with evolutionary algorithms, The 2003 Congress on Evolutionary Computation (CEC '03), 2003, pp. 312 - 319.
  8. Nguyen, H. D. , Yoshihara, I. , Yamamori, K. and Yasunaga, M. : Improved GA-based method for multiple protein sequence alignment, The 2003 Congress on Evolutionary Computation (CEC '03), 2003, pp. 1826 - 1832.
  9. Hsiao, Y. and Chuang, C. : A novel GA–based algorithm approach to fast biosequence alignment, IEEE Conference on Cybernetics and Intelligent Systems, 2004, pp. 602 - 607.
  10. Liu, LF. Huo, HW. and Wang, BS. : Aligning multiple sequences by genetic algorithm. International Conference on Communications, Circuits and Systems (ICCCAS 2004), 2004, pp. 994 - 998.
  11. Omar, MF. Salam, RA. , Rashid, NA. and Abdullah R. : Multiple sequence alignment using genetic algorithm and simulated annealing, Proceedings of International Conference on Information and Communication Technologies: From Theory to Applications,2004, pp. 455 - 456.
  12. Abdesslem, L, Soham , M. and Mohamed , B. : Multiple sequence alignment by quantum genetic algorithm , In 20th International Parallel and Distributed Processing Symposium (IPDPS 2006), 2006,pp. 241-250.
  13. Chen, Y. , Pan, Y. , Chen, J. , Liu, W. and Chen, L. : Multiple sequence alignment by ant colony optimization and divide-and-conquer, International Conference on Computational Science (2), vol. 3992 of Lecture Notes in Computer Science, 2006, pp. 646-653.
  14. Yang, C. , Jinglu, H. and Songnian, Y. : Multiple Sequence Alignment Based on Genetic Algorithms with Reserve Selection, ICNSC, 2008, 2008, pp 1511-1516.
  15. Fernando , J. , Juan , M. , Juan , A. and Miguel, A. : An Evolutionary Approach for Performing Multiple Sequence Alignment, IEEE, 2010, pp. 4244-8126
  16. Nizam, A. , Jeyakodi , R. and Kuppuswami , S. : Cyclic Genetic Algorithm for Multiple Sequence Alignment, International Journal of Research and Reviews in Electrical and Computer Engineering (IJRRECE) Vol. 1, 2010, pp. 39-44.
  17. Zahra, N. , Hamid, B. and Hassan, A. : A New Genetic Algorithm for multiple sequence alignment, Int. J. Comp. Intel. Appl. Vol. 11, 2012, pp. 1469-0268.
  18. Francisco, M. , Olega, V. and Fernando, R. : Optimizing multiple sequence alignments using a genetic algorithm based on three objectives: structural information, non-gaps percentage and totally conserved columns, Bioinformatics, vol. 82, 2013, pp. 321-332.
  19. Sanko, D. and Kruskal , J. : Time Warps, String Edits and Macromolecules, the Theory and Practice of Sequence Comparison, Addison-Wesley, 1983.
  20. Bahr, A. , Thompson, J. D, Thierry, J. C. and Poch, O , BAliBASE (Benchmark Alignment dataBASE): enhancements for repeats, transmembrane sequences and circular permutations, Nucleic Acids Res, vol. 29. , 2001, pp. 323-326.
Index Terms

Computer Science
Information Sciences

Keywords

Genetic Algorithm Multiple Sequence Alignment Dna Etc.