Realization Of Parallel Non-Alignment Based Approach To Find Longest Common Subsequence Using Hadoop MapReduce

  • Narayan Prasad Kandel

Abstract

The Longest Common Subsequence (LCS) identification of biological sequences has significant applications in bioinformatics. Due to the emerging growth in bioinformatics applications, new biological sequences with longer length have been used for processing, making it a great challenge for sequential LCS algorithms. Few parallel LCS algorithms have been proposed buttheir efficiency and effectivenessare not satisfactory with increasing complexity and size of the biological data. A parallel non-alignment based map reduce approach which help to solve the problem using distributed platform, is realized using Hadoop MapReduce.

Published
Dec 21, 2016
How to Cite
KANDEL, Narayan Prasad. Realization Of Parallel Non-Alignment Based Approach To Find Longest Common Subsequence Using Hadoop MapReduce. Zerone Scholar, [S.l.], v. 1, n. 1, p. 37-41, dec. 2016. ISSN 2542-2774. Available at: <http://zerone.pcampus.edu.np/ojs/index.php/scholar/article/view/3>. Date accessed: 28 may 2022.