An improved genetic algorithm for statistical potential function design and protein structure prediction.
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.
Department of Computer Science and Technology, Tongji University, Shanghai 201804, China. gengxin@tongji.edu.cn
Xin
X
Geng
Jihong
J
Guan
Qiwen
Q
Dong
Shuigeng
S
Zhou
D000465:Algorithms; D007700:Kinetics; D008958:Models, Molecular; D011487:Protein Conformation; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry*; D040901:Proteomics / Q000379:methods
D011506:Proteins