Title :
Aligning multiple protein sequence by an improved genetic algorithm
Author :
Zhang, Guang-Zheng ; Huang, De-Shuang
Author_Institution :
Hefei Inst. of Intelligent Machines, Chinese Acad. of Sci., Hefei, China
Abstract :
Genetic algorithm (GA) is one of the important and successful approaches in multiple sequences alignment (MSA) problem. In this paper, we propose an improved GA method, multiple small-popsize initialization strategy (MSPIS) and hybrid one-point crossover scheme (HOPCS) based GA, which can search the solution space in a very efficient manner. The experimental results show that our improved approach can obtain a better result compared with traditional GA approach in aligning multiple protein sequences problem.
Keywords :
genetic algorithms; proteins; sequences; hybrid one point crossover scheme; improved GA methods; improved genetic algorithm; multiple protein sequences; multiple sequences alignment problem; multiple small popsize initialization strategy; Biological cells; Biological information theory; Costs; Data structures; Evolution (biology); Genetic algorithms; Genetic mutations; Machine intelligence; Protein sequence; Stochastic processes;
Conference_Titel :
Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
Print_ISBN :
0-7803-8359-1
DOI :
10.1109/IJCNN.2004.1380106