Open AccessProtein Structure Prediction Based on Improved Genetic Algorithm
Author(s) -
Jiaxi Liu
Publication year - 2020
Publication title -
international journal of environmental sciences and development/international journal of environmental science and development
Language(s) - English
Resource type - Journals
ISSN - 2010-0264
DOI - 10.18178/ijesd.2020.11.9.1289
Subject(s) - protein structure prediction , genetic algorithm , algorithm , computer science , sequence (biology) , protein sequencing , protein structure , machine learning , peptide sequence , chemistry , biochemistry , gene
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.