Parallel Algorithms for Discovering Planted (l, d) Motif
Satarupa Mohanty1, Biswajit Sahoo2
1Satarupa Mohanty*, Associate Prof., School of Computer Engineering, KIIT University, Bhubaneswar, India.
2Biswajit Sahoo, Professor, School of Computer Engineering, KIIT University, Bhubaneswar, India.
Manuscript received on January 13, 2020. | Revised Manuscript received on January 21, 2020. | Manuscript published on February 10, 2020. | PP: 1452-1461 | Volume-9 Issue-4, February 2020. | Retrieval Number: D1521029420/2020©BEIESP | DOI: 10.35940/ijitee.D1521.029420
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In computational biology, motifs are short, recurring patterns of biological sequences that possess the principal character for the analysis and interpretation of various biological issues like human disease, gene function, drug design, etc. The major objectives of the motif search problem are the management, analysis, and interpretation of huge biological sequences using computational techniques from computer science and mathematics. However, detection of the motif leads to computational problems whose solutions require a substantial amount of time in one uniprocessor machine and thus, remains as one challenging problem. In this chapter, two parallel algorithms are proposed, along with its implementation detail which crucially enhances the performance of the PMSP motif search algorithm. The first approach enhances the existing algorithm by eliminating the redundant process of the computation and also, minimizes the execution time by the use of both process-level and thread-level parallelism in the implementation. The second approach is the improvement over the first one, where not only the time of computation is reduced further but also the best space utilization is achieved.
Keywords: Planted Motif Search, Process-level Parallelism, Thread-level parallelism, Bit Vector Map.
Scope of the Article: Parallel and Distributed Algorithms