Abstract
Protein structure prediction (also known as the protein folding problem) studies the way in which a protein will ‘fold’ into its natural state. Due to the enormous complexities involed in accuratly predicting protein structures, many simplifications have been proposed. The Hydrophobic-Hydrophilic (HP) method is one such method of simplifying the problem. In this chapter 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 outperforms single colony implementations. Experimental results also demonstrate that the proposed algorithms perform well in terms of network scalability.
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Chu, D., Zomaya, A. (2006). Parallel Ant Colony Optimization for 3D Protein Structure Prediction using the HP Lattice Model. In: Nedjah, N., Mourelle, L.d., Alba, E. (eds) Parallel Evolutionary Computations. Studies in Computational Intelligence, vol 22. Springer, Berlin, Heidelberg . https://doi.org/10.1007/3-540-32839-4_9
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DOI: https://doi.org/10.1007/3-540-32839-4_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32837-7
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