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Issue No. 06 - Nov.-Dec. (2013 vol. 10)
ISSN: 1545-5963
pp: 1548-1552
Mark T. Oakley , Sch. of Chem., Univ. of Birmingham, Birmingham, UK
E. Grace Richardson , Sch. of Chem., Univ. of Birmingham, Birmingham, UK
Harriet Carr , Sch. of Chem., Univ. of Birmingham, Birmingham, UK
Roy L. Johnston , Sch. of Chem., Univ. of Birmingham, Birmingham, UK
ABSTRACT
We describe the LamarckiAnt algorithm: a search algorithm that combines the features of a "Lamarckian" genetic algorithm and ant colony optimization. We have implemented this algorithm for the optimization of BLN model proteins, which have frustrated energy landscapes and represent a challenge for global optimization algorithms. We demonstrate that LamarckiAnt performs competitively with other state-of-the-art optimization algorithms.
INDEX TERMS
Proteins, Optimization, Minimization, Genetic algorithms, Bioinformatics, Computational biology,coarse-grained model proteins, Ant colony optimization
CITATION
Mark T. Oakley, E. Grace Richardson, Harriet Carr, Roy L. Johnston, "Protein Structure Optimization with a "Lamarckian"' Ant Colony Algorithm", IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 10, no. , pp. 1548-1552, Nov.-Dec. 2013, doi:10.1109/TCBB.2013.125
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