An improved genetic algorithm for statistical potential function design and protein structure prediction

Authors:
Xin Geng;Jihong Guan;Qiwen Dong;Shuigeng Zhou
Affiliations:
Department of Computer Science and Technology, Tongji University, Shanghai 201804, China;Department of Computer Science and Technology, Tongji University, Shanghai 201804, China;Shanghai Key Lab of Intelligent Information Processing, Fudan University, Shanghai 200433, China/ School of Computer Science, Fudan University, Shanghai 200433, China;Shanghai Key Lab of Intelligent Information Processing, Fudan University, Shanghai 200433, China/ School of Computer Science, Fudan University, Shanghai 200433, China
Venue:
International Journal of Data Mining and Bioinformatics
Year:
2012

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Abstract

Protein structure prediction is an important but far from being well-resolved problem in computational biology. It is generally regarded that the native structures of proteins correspond to minimum-energy states. Potential functions are useful in protein structure prediction. To obtain the optimal parameters of protein potential functions, we introduced several strategies to improve the basic Genetic Algorithm (GA). The improved GA was employed in statistical potential function design and protein structure prediction, and experimental results validate the effectiveness and efficiency of the proposed algorithm.