- 期刊
- OpenAccess
Development of Cache Oblivious Based Fast Multiple Longest Common Subsequence Technique (CMLCS) for Biological Sequences Prediction
並列摘要
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.