Abstract
Predicted amino acid sequence of the protein through its spatial structure can be attributed to a multivariable multi extreme global optimization problem. Based on AB off lattice model, a novel hybrid algorithm-MPGPSO which brings together the idea of multiple populations with the improved genetic algorithm and particle swarm optimization algorithm is presented in this paper for searching for the ground state structure of protein. The new algorithm taking advantages of the idea of best of best to enhance the algorithm’s search capability. Experimental results are effective when it is applied to predict the best 3D structure of real protein sequences.
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Zhou, C., Hu, T., Zhou, S. (2014). Protein Structure Prediction Based on Improved Multiple Populations and GA-PSO. In: Pan, L., Păun, G., Pérez-Jiménez, M.J., Song, T. (eds) Bio-Inspired Computing - Theories and Applications. Communications in Computer and Information Science, vol 472. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45049-9_105
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DOI: https://doi.org/10.1007/978-3-662-45049-9_105
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-45048-2
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