Volume 11 Number 9 (Sep. 2020)
IJESD 2020 Vol.11(9): 450-454 ISSN: 2010-0264
doi: 10.18178/ijesd.2020.11.9.1289

Protein Structure Prediction Based on Improved Genetic Algorithm

Jiaxi Liu
Abstract— The prediction of protein three-dimensional structure from amino acid sequence has been a challenge problem in bioinformatics, owing to the many potential applications for robust protein structure prediction methods. Protein structure prediction is essential to bioscience, and its research results are important for other research areas. Methods for the prediction an才d design of protein structures have advanced dramatically. The prediction of protein structure based on average hydrophobic values is discussed and an improved genetic algorithm is proposed to solve the optimization problem of hydrophobic protein structure prediction. An adjustment operator is designed with the average hydrophobic value to prevent the overlapping of amino acid positions. Finally, some numerical experiments are conducted to verify the feasibility and effectiveness of the proposed algorithm by comparing with the traditional HNN algorithm.

Index Terms— Protein structure prediction, genetic algorithm, amino acid hydrophobicity.

Jiaxi Liu is with the Masters School, 49 Clinton Avenue, Dobbs Ferry, NY 10522, USA (e-mail: jiaxi.liu@mastersny.org).


Cite: Jiaxi Liu, " Protein Structure Prediction Based on Improved Genetic Algorithm," International Journal of Environmental Science and Development vol. 11, no. 9, pp. 450-454, 2020.

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

 General Information

  • ISSN: 2010-0264 (Print); 2972-3698 (Online)
  • Abbreviated Title: Int. J. Environ. Sci. Dev.
  • Frequency: Bimonthly
  • DOI: 10.18178/IJESD
  • Editor-in-Chief: Prof. Richard Haynes
  • Managing Editor: Ms. Cherry L. Chen
  • Indexing: Scopus, Google Scholar, CNKI, ProQuest, EBSCO, etc. 

  • E-mail: ijesd@ejournal.net      

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