Rule Based Matrix Insertion Deletion Scheme for Improved Bio Molecular Computing
Kotteeswaran C1, Khanaa V2, Rajesh A3
1Kotteeswaran C, Research Scholar, Department of Computer Science and Engineering, BHIER, Chennai (Tamil Nadu), India.
2Khanaa V, Professor & Dean, Department of IT, BHIER, Chennai (Tamil Nadu), India.
3Rajesh A, Principal, C. Abdul Hakeem College of Engineering & Technology, Vellore (Tamil Nadu), India.
Manuscript received on 22 May 2019 | Revised Manuscript received on 08 June 2019 | Manuscript Published on 15 June 2019 | PP: 376-379 | Volume-8 Issue-1S2 May 2019 | Retrieval Number: A00880581S219/2019©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: The problem of RNA editing has been well studied and there are number of approaches discussed earlier but suffer to achieve higher performance. To improve the performance an rule based approach is discussed in this paper. The RNA sequence generally consists of DNA sequences being represented as chain of string values. The malformed sequence has been used to identify the presence of any disease and such malformation encourages the occurrence of any disease to be happen. The rule based approach reads the RNA sequence and verifies the presence of tiny sequences specified in the rule set. The presence of malformed sequence has been deleted using matrix insertion deletion and has been added to produce new sequence of RNA. The classification is performed based on the RNA Sequence Support measure (RSSM) being estimated towards different class of sequences. The proposed method improves the performance of bio molecular computing to support the disease prediction.
Keywords: DNA, RNA, Bio Molecular Computing, RSSM.
Scope of the Article: Cloud Computing and Networking