Analysis of toy model for protein folding based on particle swarm optimization algorithm
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
Protein structure prediction in lattice models with particle swarm optimization
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Protein structure prediction using particle swarm optimization and a distributed parallel approach
Proceedings of the 3rd workshop on Biologically inspired algorithms for distributed systems
Protein structure prediction using distributed parallel particle swarm optimization
Natural Computing: an international journal
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This article presents the implementation of a bio-inspired algorithm, which is the algorithm of particle swarm optimization (PSO) in with the objective of minimizing the function of conformational energy ECEPP/3 for the protein folding problem (PFP) for real conformations considering structural restrictions. In this case, using a representation of torsion angles of the skeleton and the side chains, applying the sequence of amino acid of the peptide leu-enkephalin for the prediction of 3D structure of minimum energy. The quality of the results is compared with other techniques reported in literature. Subsequently, the PSO is used to predict the structure of unknown proteins.