Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Fundamentals of neural networks: architectures, algorithms, and applications
Fundamentals of neural networks: architectures, algorithms, and applications
SODA '97 Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms
Ant algorithms for discrete optimization
Artificial Life
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Tabu Search
Digital Principles and Applications
Digital Principles and Applications
A complete and effective move set for simplified protein folding
RECOMB '03 Proceedings of the seventh annual international conference on Research in computational molecular biology
Genetic Algorithm for 3D Protein Folding Simulations
Proceedings of the 5th International Conference on Genetic Algorithms
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
An Ant Colony Optimization Algorithm for the 2D HP Protein Folding Problem
ANTS '02 Proceedings of the Third International Workshop on Ant Algorithms
The algorithmics of folding proteins on lattices
Discrete Applied Mathematics - Special issue: Computational molecular biology series issue IV
Genetic programming neural networks: A powerful bioinformatics tool for human genetics
Applied Soft Computing
Crowding clustering genetic algorithm for multimodal function optimization
Applied Soft Computing
An improved ant colony optimisation algorithm for the 2D HP protein folding problem
AI'03 Proceedings of the 16th Canadian society for computational studies of intelligence conference on Advances in artificial intelligence
An Immune Algorithm for Protein Structure Prediction on Lattice Models
IEEE Transactions on Evolutionary Computation
Novel Memetic Algorithm for Protein Structure Prediction
AI '09 Proceedings of the 22nd Australasian Joint Conference on Advances in Artificial Intelligence
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
An evolutionary model based on hill-climbing search operators for protein structure prediction
EvoBIO'10 Proceedings of the 8th European conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Conflict resolution based global search operators for long protein structures prediction
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part I
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
An improved multiobjectivization strategy for HP model-based protein structure prediction
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
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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This paper introduces the hydrophobic-polar (HP) models and several natural computing approaches. The biological background of the protein structure prediction, the Levinthal paradox and HP model are firstly revised. Subsequently the evolutionary algorithm, memetic algorithm, ant colony optimization algorithm, tabu search, self organizing map-based iterative approaches and the typical chain growth computing approaches are reviewed. The advantages/disadvantages of various computing approaches and the current optimal results are introduced. Finally, the promising model and computing approaches are discussed.