A cooperative fast annealing coevolutionary algorithm for protein motif extraction
By integrating the cooperative approach with the fast annealing coevolutionary algorithm (FAEA), a so-called cooperative fast annealing coevolutionary algorithm (CFACA) is presented in this paper for the purpose of solving high-dimensional problems. After the partition of the search space in CFACA,...
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Published in | Chinese science bulletin Vol. 52; no. 3; pp. 318 - 323 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
School of Chemistry and Chemical Engineering, Sun Yat-Sen University, Guangzhou 510275, China
01.02.2007
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Subjects | |
Online Access | Get full text |
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Summary: | By integrating the cooperative approach with the fast annealing coevolutionary algorithm (FAEA), a so-called cooperative fast annealing coevolutionary algorithm (CFACA) is presented in this paper for the purpose of solving high-dimensional problems. After the partition of the search space in CFACA, each smaller one is then searched by a separate FAEA. The fitness function is evaluated by combining sub-solutions found by each of the FAEAs. It demonstrates that the CFACA outperforms the FAEA in the domain of function optimization, especially in terms of convergence rate. The current algorithm is also applied to a real optimization problem of protein motif extraction. And a satisfactory result has been obtained with the accuracy of prediction achieving 67.0%, which is in agreement with the result in the PROSITE database. |
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Bibliography: | Q518.1 global optimization, cooperative approach, fast annealing, evolutionary algorithm, protein motif 11-1785/N |
ISSN: | 1001-6538 1861-9541 |
DOI: | 10.1007/s11434-007-0047-x |