Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Nature inspired optimization algorithm for prediction of “minimum free energy” “RNA secondary structure”

Nature inspired optimization algorithm for prediction of “minimum free energy” “RNA secondary... 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Reliable Intelligent Environments Springer Journals

Nature inspired optimization algorithm for prediction of “minimum free energy” “RNA secondary structure”

Loading next page...
 
/lp/springer-journals/nature-inspired-optimization-algorithm-for-prediction-of-minimum-free-v5OMlz9zee
Publisher
Springer Journals
Copyright
Copyright © 2019 by Springer Nature Switzerland AG
Subject
Computer Science; Performance and Reliability; Software Engineering/Programming and Operating Systems; Artificial Intelligence; Simulation and Modeling ; User Interfaces and Human Computer Interaction; Health Informatics
ISSN
2199-4668
eISSN
2199-4676
DOI
10.1007/s40860-019-00091-0
Publisher site
See Article on Publisher Site

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.

Journal

Journal of Reliable Intelligent EnvironmentsSpringer Journals

Published: Sep 21, 2019

References