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DNA Sequence Data Compression Method Based on Memetic Algorithm |
Tan Li Sun Ji-feng Guo Li-hua |
School of Electronic and Information Engineering, South China University of Technology, Guangzhou 510641, China |
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Abstract A DNA sequence compression method based on Collaborative Particle swarm optimization-based Memetic Algorithm (CPMA) is proposed. CPMA adopts the Comprehensive Learning Particle Swarm Optimization (CLPSO) as the global search and a Dynamic Adjustive Chaotic Search Operator (DACSO) as the local search respectively. In CPMA, it looks for the global optimal code book based on Extended Approximate Repeat Vector (EARV), by which the DNA sequence is compressed. Experimental results demonstrate better performance of HMPSO than the other optimization algorithms, and it is very close to the global optimization point in most of the test functions adopted by the paper. The compression performance of the method based on CPMA is markedly improved compared to many of the classical DNA sequence compression algorithms.
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Received: 12 March 2013
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Corresponding Authors:
Tan Li
E-mail: t.li07@mail.scut.edu.cn
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