Abstract
In this paper, the 2-Species Duplication-Loss Small Phylogeny Problem is studied. By introducing an alignment algorithm, a labeling algorithm and three smart mutate operators, a genetic algorithm G2SP is presented. Algorithm G2SP adopts the method of combining the general operator and the smart ones. The general operator maintains the population diversity effectively, while the smart ones improve population convergence and make it evolve to the optimal solution more quickly. The tRNA and rRNA gene data of six kinds of real bacterium were used to test the performance of algorithms. The experimental results indicate that the G2SP algorithm can get fewer evolution cost than the PBLB algorithm proposed by Holloway et al., and it is an effective method for solving the 2-species duplication-loss small phylogeny problem.
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Acknowledgments
The authors are grateful to anonymous referees for their helpful comments. This research is supported by the National Natural Science Foundation of China under Grant No. 61363035 and No. 61502111, Guangxi Natural Science Foundation under Grant No. 2015GXNSFAA139288, No. 2013GXNSFBA019263 and No. 2012GXNSFAA053219, Research Fund of Guangxi Key Lab of Multisource Information Mining and Security No. 14-A-03-02 and No. 15-A-03-02, “Bagui Scholar” Project Special Funds, Guangxi Collaborative Innovation Center of Multi-source Information Integration and Intelligent Processing.
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Wu, J., Wang, J. (2016). A Practical Algorithm for the 2-Species Duplication-Loss Small Phylogeny Problem. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theories and Application. ICIC 2016. Lecture Notes in Computer Science(), vol 9771. Springer, Cham. https://doi.org/10.1007/978-3-319-42291-6_33
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DOI: https://doi.org/10.1007/978-3-319-42291-6_33
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