A hybrid particle swarm optimization based memetic algorithm for DNA sequence compression

Verfasser / Beitragende:
[Li Tan, Jifeng Sun, Xueke Tong]
Ort, Verlag, Jahr:
2015
Enthalten in:
Soft Computing, 19/5(2015-05-01), 1255-1268
Format:
Artikel (online)
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024 7 0 |a 10.1007/s00500-014-1338-1  |2 doi 
035 |a (NATIONALLICENCE)springer-10.1007/s00500-014-1338-1 
245 0 2 |a A hybrid particle swarm optimization based memetic algorithm for DNA sequence compression  |h [Elektronische Daten]  |c [Li Tan, Jifeng Sun, Xueke Tong] 
520 3 |a Due to the recent advancements in high- throughput sequencing technologies, biomedical research is faced with ever increasing quantities of data, and the storage or transmission of the huge amount of data is one of the concerns. So, we presented a novel hybrid particle swarm optimization based memetic algorithm (HPMA) for DNA sequence compression. In HPMA, within the framework of the memetic algorithm, dynamic comprehensive learning particle swarm optimization method is used for global search, and two adaptive local search operators including center symmetry mutation differential evolution operator and adaptive chaotic search operator work in a cooperative way. HPMA looks for the global optimal code book based on extended approximate repeat vector, by which the DNA sequence will be compressed. Experiments were conducted on 19 high-dimensional functions and 11 real DNA sequences. The results show that HPMA is more competitive in both the performance and scalability, and also attains better compression ability than other representative DNA-specific algorithms on DNA sequence data. 
540 |a Springer-Verlag Berlin Heidelberg, 2014 
690 7 |a Extended approximate repeat vector  |2 nationallicence 
690 7 |a Center symmetry mutation differential evolution operator  |2 nationallicence 
690 7 |a Adaptive chaotic search operator  |2 nationallicence 
690 7 |a DNA sequence compression  |2 nationallicence 
700 1 |a Tan  |D Li  |u School of Electronic and Information Engineering, South China University of Technology, 510641, Guangzhou, People's Republic of China  |4 aut 
700 1 |a Sun  |D Jifeng  |u School of Electronic and Information Engineering, South China University of Technology, 510641, Guangzhou, People's Republic of China  |4 aut 
700 1 |a Tong  |D Xueke  |u School of Electronic and Information Engineering, South China University of Technology, 510641, Guangzhou, People's Republic of China  |4 aut 
773 0 |t Soft Computing  |d Springer Berlin Heidelberg  |g 19/5(2015-05-01), 1255-1268  |x 1432-7643  |q 19:5<1255  |1 2015  |2 19  |o 500 
856 4 0 |u https://doi.org/10.1007/s00500-014-1338-1  |q text/html  |z Onlinezugriff via DOI 
898 |a BK010053  |b XK010053  |c XK010000 
900 7 |a Metadata rights reserved  |b Springer special CC-BY-NC licence  |2 nationallicence 
908 |D 1  |a research-article  |2 jats 
949 |B NATIONALLICENCE  |F NATIONALLICENCE  |b NL-springer 
950 |B NATIONALLICENCE  |P 856  |E 40  |u https://doi.org/10.1007/s00500-014-1338-1  |q text/html  |z Onlinezugriff via DOI 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Tan  |D Li  |u School of Electronic and Information Engineering, South China University of Technology, 510641, Guangzhou, People's Republic of China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Sun  |D Jifeng  |u School of Electronic and Information Engineering, South China University of Technology, 510641, Guangzhou, People's Republic of China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Tong  |D Xueke  |u School of Electronic and Information Engineering, South China University of Technology, 510641, Guangzhou, People's Republic of China  |4 aut 
950 |B NATIONALLICENCE  |P 773  |E 0-  |t Soft Computing  |d Springer Berlin Heidelberg  |g 19/5(2015-05-01), 1255-1268  |x 1432-7643  |q 19:5<1255  |1 2015  |2 19  |o 500