Computational Optimization and Analysis of Functional Bioinformatics using Parallel Algorithm
Ujjwala Hemant Mandekar1, Sunanda P Khandait2, Leena H Patil3
1Ujjwala H. Mandekar, Research Scholar, Department of Computer Science & Engg., Priyadarshini Institute of Engg & Tech., Nagpur, India
2Sunanda P. Khandait, Professor & Head of Information Technology Department of, KDK Engineering College, Nagpur, India
3Leena H Patil, Associate Professor, Department of Computer Science & Engg., Priyadarshini Institute of Engg & Tech, Nagpur, India
Manuscript received on 02 June 2019 | Revised Manuscript received on 07 June 2019 | Manuscript published on 30 June 2019 | PP: 1906-1911 | Volume-8 Issue-8, June 2019 | Retrieval Number: F3418048619/19©BEIESP
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© 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: With the recent development in the cellular biology, the importance of RNA structure prediction has been tremendously increased. RNA has many important functions in cellular reaction. It plays an important role in protein as well as metabolic reactions. Also RNA structure prediction are useful to innovate newer methodologies for the treatment of many diseases like Tumour, HIV, Ebola etc. As a result many researchers are working in this area to invent RNA structure prediction algorithms. Almost in past three decades scientists have proposed RNA structure prediction algorithms. In this paper we are presenting a brief review of available RNA structure prediction algorithms. Also, we are presenting our newly developed algorithm for RNA tertiary structure prediction which uses parallel computing to speed up the computational processing. This newly developed algorithm is capable of predicting tertiary structure for very long sequences, where other existing methods face a problem of memory crash.
Keywords: RNA Tertiary Structure, OpenMP, Kissing Pairs, Base Pairs, Loop Similarity.
Scope of the Article: Computational Biology