Protein Structure Prediction based on An Improved genetic Algorithm
Protein structure prediction problem has been focused much attention upon. Genetic algorithm as a useful computational tool for addressing optimization tasks has been applied to this domain. In this paper, considering the deficiency of simple genetic algorithm, such as prematurity and slow convergence, we propose HPGA/GBX which is an improvement of GA and the algorithm is evaluated with three standard test functions. The experimental results show the effectiveness of the proposed method. Then HPGA/GBX is applied to protein tertiary structure prediction and compared with other methods. The target protein in this paper is Met-enkephalin. The results show that HPGA/GBX is a very good method in finding the minimum energy of small protein.
genetic algorithm protein structure prediction crossover operator
Yunling Liu Lan Tao
College of Information and Electrical Engineering China Agricultural University, Beijing 100083, Chi Faculty Information Engineering, Shenzhen University, Shenzhen 518060, China
国际会议
上海
英文
577-580
2008-05-16（万方平台首次上网日期，不代表论文的发表时间）