Paper Info
Title
Nature inspired optimization algorithm for prediction of "minimum free energy" "RNA secondary structure".
Abstract
Over the last few years, many optimization algorithms have been developed to predict the optimal secondary structure of ribonucleic acid (RNA) with “minimum free energy” (MFE). These algorithms are either inspired by dynamic programming or by meta-heuristic techniques. RNA participates in several biological activities in the organism. These activities involve protein synthesis, understanding the functional behavior of RNA molecules, coding, decoding and gene expression, carrier of transferring genetic information, formation of protein, catalyst in biomedical reactions and structural molecule in cellular organelles, transcription, etc. Beside the said activities, the major role of RNA is in developing new drugs and understanding several diseases occurred due to genetic disorder and viruses. For the above said activities, it is required to predict the correct RNA secondary structure having minimum free energy with desired prediction accuracy. This paper presents a meta-heuristic optimization algorithm to obtain the optimal secondary structure of RNA with required functionality and requires less time than the others in the literature. The performance of the proposed algorithm is checked with different existing state-of-the-art techniques. It is found that the proposed algorithm gives better results against the other techniques.
Year
DOI
Venue
2019
10.1007/s40860-019-00091-0
Journal of Reliable Intelligent Environments
Keywords
Field
DocType
Optimization, EAMD, “Minimum free energy”, Adaptive learning, Pseudoknots
Computer science,Algorithm,Real-time computing,Optimization algorithm,Nucleic acid secondary structure,Minimum free energy
Journal
Volume
Issue
ISSN
5
4
2199-4668
Citations 
PageRank 
References 
1
0.35
0
Authors
4
Name
Order
Citations
PageRank
Ashish Tripathi172.51
K. K. Mishra2407.98
Shailesh Tiwari3146.95
P. C. Vashist410.35