RNA secondary structure prediction using Fruit Fly Optimization Algorithm

被引:0
作者
Chatterjee, Sajib [1 ]
Rabeya, Sayla Parvin [1 ]
Halder, Setu [1 ]
Mondal, Madhab [1 ]
Sujana, Farjana Yesmin [1 ]
机构
[1] North Western Univ, Dept Comp Sci & Engn, Khulna, Bangladesh
来源
2020 IEEE REGION 10 SYMPOSIUM (TENSYMP) - TECHNOLOGY FOR IMPACTFUL SUSTAINABLE DEVELOPMENT | 2020年
关键词
RNA secondary structure prediction; Fruit fly optimization algorithm; Minimum Gibbs free energy; Repair function; efficiency;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
RNA Secondary Structure Prediction (RSSP) is an optimization problem, where a stable secondary structure is acquired from an RNA primary sequence. Many exact, heuristic and metaheuristic algorithms established in recent years to solve the RSSP problem. We have resolved an accession based on metaheuristic algorithm named Fruit Fly Optimization algorithm to solve the RNA secondary structure prediction problem. FOA is a population-based metaheuristic that works better than all other related existing algorithms and has been employed in different optimization problems. We have redesigned the operators of the FOA algorithm and calculated the minimum Gibbs free energy (Delta G) of the structure to solve the RNA secondary structure problem. We have a Repair function which is known as novel operator that is used to verify and expel the repeated stem from RNA sequence, which is very time-efficient. Every quality of the solutions and spending time are calculated in designing the operators and the repair function. The raised methodology gives efficiency, robustness, and effectiveness in solving the RSSP problem.
引用
收藏
页码:1738 / 1742
页数:5
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