NDLI: DNA fragment assembly using an ant colony system algorithm

Content Provider	IEEE Xplore Digital Library
Author	Meksangsouy, P. Chaiyaratana, N.
Copyright Year	2003
Description	Author affiliation: Dept. of Math., King Mongkut's Inst. of Technol. North Bangkok, Thailand (Meksangsouy, P.)
Abstract	This work presents the use of an ant colony system algorithm in a DNA (deoxyribonucleic acid) fragment assembly. The assembly problem is a combinatorial optimisation problem where the aim of the search is to find the right order and orientation of each fragment in the fragment ordering sequence that leads to the formation of a consensus sequence. In this paper, an asymmetric ordering representation is proposed where a path cooperatively generated by all ants in the colony represents the search solution. The optimality of the fragment layout obtained is then determined from the sum of overlap scores calculated for each pair of consecutive fragments in the layout. Two types of assembly problem are investigated: single-contig and multiple-contig problems. The simulation results indicate that in single-contig problems, the performance of the ant colony system algorithm is approximately the same as that of a nearest neighbour heuristic algorithm. On the other hand, the ant colony system algorithm outperforms the nearest neighbour heuristic algorithm when multiple-contig problems are considered.
Sponsorship	Air Force Iffice of Sci. Res. Asian Office of Aerospace Res and Development Army Res. Office - Far East CISCO Evoluationary Programming Soc. IEE Inst. of Engineers, Australia IEEE Neural Networks Soc. Univ. of New South Wales
Starting Page	1756
Ending Page	1763
File Size	632070
Page Count	8
File Format	PDF
ISBN	0780378040
DOI	10.1109/CEC.2003.1299885
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-12-08
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	DNA Assembly systems Sequences Humans Genomics Bioinformatics Heuristic algorithms Genetics Mathematics Organisms
Content Type	Text
Resource Type	Article

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