Effectiveness Of Ssaha Algorithm For Searching Motif In Large Databases Of Dna Sequences

Khumukcham Robindro¹ , Ashoke Das²

1. Dept. of Computer Science, Manipur University (A Central University), Manipur, India.
2. Department of Mathematics, Raiganj University, Raiganj, India.

Correspondence should be addressed to: rbkh@manipuruniv.ac.in.

Section:Research Paper, Product Type: Isroset-Journal
Vol.5 , Issue.4 , pp.79-87, Aug-2017

Online published on Aug 30, 2017

Copyright © Khumukcham Robindro, Ashoke Das . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Motif finding has become a very significant area of study in the post genomic era because of its various applications and usage in the bioinformatics research. The volume of the biological data is also on the ever increasing trend. Many algorithms have been proposed for efficient motif findings. In this paper, an approach is proposed to use a fast search method called SSAHA for motif finding. SSAHA is an efficient algorithm which effectively searches a given query in large databases containing multiple gigabases of DNA. In our approach, the effectiveness of SSAHA algorithm in searching large databases of DNA is exploited for searching motif in large databases of DNA sequences.

Key-Words / Index Term :
Motif, Algorithm, SSAHA, DNA, Database

References :
[1] Zemin Ning, Anthony J. Cox, and James C. Mullikin (2001) SSAHA: A First Search Method for Large DNA Databases
[2] Altschul, S.F., Gish, W., Miller, W., Myers, E.W., and Lipman, D.J.(1990). Basic Local Alignment Search Tool. J. Mol. Biol.215: 403–410.
[3] Altschul, S.F., Madden, T.L., Schäffer, A.A., Zhang, J., Zhang, Z.,Miller, W., and Lipman, D.J. (1997). Gapped BLAST and PSI-BLAST: A new generation of protein database search programs.Nucleic Acids Res. 25: 3389–3402.
[4] Benson, G. (1999). Tandem Repeats Finder: A program to analyzeDNA sequences. Nucleic Acids Res. 27: 573–580.
[5] Delcher, A.L., Kasif, S., Fletschmann, R.D., Peterson, J., White, O.,and Salzberg, S. (1999). Alignment of whole genomes. NucleicAcids Res. 27: 2369–2376.
[6] Gusfield, D. (1997). Algorithms on strings, trees and sequences: Computer science and computational biology. Cambridge University Press,Cambridge, UK.
[7] Knuth, D.E. (1998). The art of computer programming vol. 3: Sorting and searching. Addison-Wesley, Reading, MA.
[8] Lipman, D.J. and Pearson, W.R. (1985). Rapid and sensitive protein similarity searches. Science 227: 1435–1441.
[9] Zhang, Z., Schwartz, S., Wagner, L., and Miller, W. (2000). A greedy algorithm for aligning DNA sequences. J. Comp. Biol. 7: 203–214
[10] Anjali Mohapatra, P.M. Mishra, S. Padhy (2007): Motif Search in DNA Sequences Using Generalized Suffix Tree, 10th International Conference on Information Technology.
[11] Elena Zheleva and A.N.Arslan, 2005, Fast motif search in protein sequence database, Department of Computer Science, University of Vermont.
[12] N. S. Dasari, R. Desh, and Z. M.( 2010) An efficient multicore implementation of planted motif problem. In Proceedings of the International Conference On High Performance Computing and Simulation, pages 9–15.
[13] Sanguthevar Rajasekaran, Sudha Balla, Chun-His Huang(2004): Exact Algorithms for Planted Motif Problems.Dept. of Computer Science and engineering, University of Connecticut.
[14] J. Davila, S. Balla, and S. Rajasekaran.( 2007) Fast and practical algorithms for planted (l, d) motif search. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 4:544–552 .