Improved Niche Genetic Algorithm for Protein Structure Prediction

Due to the complexity and variety of protein structure, the protein structure prediction (PSP) is a challenging problem in the field of bioinformatics. In this paper, we adopt an improved niche genetic algorithm for protein structure prediction, the niche genetic algorithm (NGA) bonds with some improvement strategies, which have a competitive selection, a random crossover and random linear mutation operator. These improvement strategies can maintain the population diversity and avoid the shortcomings of the Niche Genetic algorithm that stagnate evolution and be caught in local optimum. And our experiment gains some better results than other algorithms with the Fibonacci sequence and the real protein sequence. Finally, the experiment results illustrate the efficiency of this algorithm on the Fibonacci sequence and the real protein sequence.

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