Information Exchange in Multi Colony Ant Algorithms
IPDPS '00 Proceedings of the 15 IPDPS 2000 Workshops on Parallel and Distributed Processing
HAS-SOP: Hybrid Ant System for the Sequential Ordering Problem
HAS-SOP: Hybrid Ant System for the Sequential Ordering Problem
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
A hybrid immune-based system for the protein folding problem
EvoCOP'07 Proceedings of the 7th European conference on Evolutionary computation in combinatorial optimization
Information Sciences: an International Journal
Parallel Ant Colony Optimization on Graphics Processing Units
Journal of Parallel and Distributed Computing
Cross-lattice behavior of general ACO folding for proteins in the HP model
Proceedings of the 28th Annual ACM Symposium on Applied Computing
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The Protein Folding Problem studies the way in which a protein - a chain of amino acids - will 'fold' into its natural state. Predicting the way in which various proteins fold can be fundamental in developing treatments of diseases such as Alzeihmers and Systic Fibrosis. Classical solutions to calculating the final conformation of a protein structure are resource-intensive. The Hydrophobic-Hydrophilic (HP) method is one way of simplifying the problem. We introduce a novel method of solving the HP protein folding problem in both two and three dimensions using Ant Colony Optimizations and a distributed programming paradigm. Tests across a small number of processors indicate that the multiple colony distributed ACO (MACO) approach is scalable and outperforms single colony implementations.