A Standard GA Approach to Native Protein Conformation Prediction
Proceedings of the 6th International Conference on Genetic Algorithms
Multimeme Algorithms for Protein Structure Prediction
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
A Novel Genetic Algorithm for HP Model Protein Folding
PDCAT '05 Proceedings of the Sixth International Conference on Parallel and Distributed Computing Applications and Technologies
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Differential Evolution: In Search of Solutions (Springer Optimization and Its Applications)
Differential Evolution: In Search of Solutions (Springer Optimization and Its Applications)
Protein Structure Prediction Using Evolutionary Algorithms Hybridized with Backtracking
IWANN '03 Proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks: Part II: Artificial Neural Nets Problem Solving Methods
An enhanced genetic algorithm for protein structure prediction using the 2d hydrophobic-polar model
EA'05 Proceedings of the 7th international conference on Artificial Evolution
An Immune Algorithm for Protein Structure Prediction on Lattice Models
IEEE Transactions on Evolutionary Computation
Multiobjectivizing the HP model for protein structure prediction
EvoCOP'12 Proceedings of the 12th European conference on Evolutionary Computation in Combinatorial Optimization
Locality-based multiobjectivization for the HP model of protein structure prediction
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Protein folding with cellular automata in the 3D HP model
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
A multiple minima genetic algorithm for protein structure prediction
Applied Soft Computing
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We used Differential Evolution (DE) for the problem of protein structure prediction. We employed the HP model to represent the folding conformations of a protein in a lattice. In this model the nature of amino acids is reduced considering only two types: hydrophobic residues (H) and polar residues (P), which is based on the recognition that hydrophobic interactions are a dominant force in protein folding. Given a primary sequence of amino acids, the problem is to search for the folding structure in the lattice that minimizes an energy potential. This energy reflects the fact that the hydrophobic amino acids have a propensity to form a hydrophobic core. The complexity of the problem has been shown to be NP-hard, with minimal progress achieved in this category of ab initio folding. We combined DE with methods to transform illegal protein conformations to feasible ones, showing the capabilities of the hybridized DE with respect to previous works.