Genetic algorithms with sharing for multimodal function optimization
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Surmounting the Multiple-Minima Problem in Protein Folding
Journal of Global Optimization
A Standard GA Approach to Native Protein Conformation Prediction
Proceedings of the 6th International Conference on Genetic Algorithms
The algorithmics of folding proteins on lattices
Discrete Applied Mathematics - Special issue: Computational molecular biology series issue IV
Handbook of Computational Molecular Biology (Chapman & All/Crc Computer and Information Science Series)
Differential evolution for protein structure prediction using the HP model
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation - Volume Part I
Fitness sharing and niching methods revisited
IEEE Transactions on Evolutionary Computation
An Immune Algorithm for Protein Structure Prediction on Lattice Models
IEEE Transactions on Evolutionary Computation
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Protein structure prediction (PSP) has a large potential for valuable biotechnological applications. However the prediction itself encompasses a difficult optimization problem with thousands of degrees of freedom and is associated with extremely complex energy landscapes. In this work a simplified three-dimensional protein model (hydrophobic-polar model, HP in a cubic lattice) was used in order to allow for the fast development of a robust and efficient genetic algorithm based methodology. The new methodology employs a phenotype based crowding mechanism for the maintenance of useful diversity within the populations, which resulted in increased performance and granted the algorithm multiple solutions capabilities. Tests against several benchmark HP sequences and comparative results showed that the proposed genetic algorithm is superior to other evolutionary algorithms. The proposed algorithm was then successfully adapted to an all-atom protein model and tested on poly-alanines. The native structure, an alpha helix, was found in all test cases as a local or a global minimum, in addition to other conformations with similar energies. The results showed that optimization strategies with multiple solutions capability present two advantages for PSP applications. The first one is a more efficient investigation of complex energy landscapes; the second one is an increase in the probability of finding native structures, even when they are not at the global optimum.