PSPGA: A New Method for Protein Structure Prediction based on Genetic Algorithm

Document Type: Original Article


1 Department of Computer Engineering, Faculty of Engineering, Golestan University, Gorgan, Iran.

2 Department of Nanotechnology and Advanced Materials, Materials and Energy Research Center, Karaj, Iran


Bioinformatics is a new science that uses algorithms, computer software and databases in order to solve biological problems, especially in the cellular and molecular areas. Bioinformatics is defined as the application of tools of computation and analysis to the capture and interpretation of biological data. Protein Structure Prediction (PSP) is one of the most complex and important issues in bioinformatics, and extensive researches has been done to solve this problem using evolutionary algorithms. In this paper, we propose a genetic based method in order to solve protein structure prediction problem with increasing the accuracy of prediction, using a crossover operator based on pattern mask. Further, we compare two genetic based method to evaluate the proposed method. The results of the implementation of our proposed algorithm on five standard test sequences show that the use of a pattern mask-based crossover operator in the genetic algorithm can significantly improve the accuracy compared to previous similar algorithms.