DocumentCode :
2136530
Title :
The novel ant colony system for DNA sequencing by hybridization
Author :
Lian-Ming Mou ; Xi-Li Dai
Author_Institution :
Key Lab. of Numerical Simulation of Sichuan Province, Neijiang Normal Univ., Neijiang, China
fYear :
2013
fDate :
23-25 July 2013
Firstpage :
580
Lastpage :
584
Abstract :
DNA sequencing by hybridization (SBH) has been a very challenging problem in computational biology. We propose a novel ant colony system through a detailed analysis of SBH. Firstly, the SBH problem is subtly transformed into a selective asymmetric traveling salesman problem with constraint condition. Then, the local mutation and neighborhood searching technique are introduced to improve the solution quality and accelerate the convergence according to the characteristic of SBH. Finally, the optimal DNA sequence is obtained by using an effective results-post-processing technique. Experimental results from extensive simulations confirm that our proposed method is significantly superior to the state-of-the-art methods in accuracy and stability.
Keywords :
DNA; ant colony optimisation; biology computing; travelling salesman problems; DNA sequencing by hybridization; SBH; asymmetric traveling salesman problem; computational biology; local mutation technique; neighborhood searching technique; novel ant colony system; optimal DNA sequence; Acceleration; DNA; Educational institutions; Probes; Search problems; Sequential analysis; Traveling salesman problems; DNA sequencing by hybridization; ant colony system; local mutation; neighborhood searching;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2013 Ninth International Conference on
Conference_Location :
Shenyang
Type :
conf
DOI :
10.1109/ICNC.2013.6818043
Filename :
6818043
Link To Document :
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