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2012 (Vol. 4, Issue: 09)
Article Information:

Development of Cache Oblivious Based Fast Multiple Longest Common Subsequence Technique(CMLCS) for Biological Sequences Prediction

A. Sumathi and N. K. Sakthivel
Corresponding Author:  A. Sumathi 

Key words:  Dominant point method, dynamic programming, LCS, MLCS, , ,
Vol. 4 , (09): 1198-1204
Submitted Accepted Published
January 11, 2012 February 06, 2012 May 01, 2012
Abstract:

A biological sequence is a single, continuous molecule of nucleic acid or protein. Classical methods for the Multiple Longest Common Subsequence problem (MLCS) problem are based on dynamic programming. The Multiple Longest Common Subsequence problem (MLCS) is used to find the longest subsequence shared between two or more strings. For over 30 years, significant efforts have been made to find efficient algorithms for the MLCS problem. Many of them have been proposed for the general case of any given number of strings. They could benefit greatly from improving their computation times. (Qingguo et al.,) proposed a new algorithm for the general case of Multiple LCS problem, which is finding the LCS of any number of strings. This algorithm is based on the dominant point approach and employs a fast divide-and-conquers technique to compute the dominant points. From this existing work, it is observed that, when this approach is applied to a case of three strings, this algorithm demonstrates the same performance as the fastest existing MLCS algorithm. When applied to more than three strings, this technique is significantly faster than the existing sequential methods, reaching up to 2-3 orders of magnitude faster speed on large-size problems. However, from our experimental results, it is observed that as the size of the Data Set is increasing, its performance decreases in terms of execution time. To overcome this major issue, we have developed an efficient model called Cache Oblivious based Multiple Longest Common Subsequence (CMLCS). From our experimental results, it is observed that our proposed work performs better as compared with the existing system in terms of Execution Time and Memory Usage.
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  Cite this Reference:
A. Sumathi and N. K. Sakthivel, 2012. Development of Cache Oblivious Based Fast Multiple Longest Common Subsequence Technique(CMLCS) for Biological Sequences Prediction.  Research Journal of Applied Sciences, Engineering and Technology, 4(09): 1198-1204.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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