DNA fragment assembly: an ant colony system approach

Authors:
Wannasak Wetcharaporn;Nachol Chaiyaratana;Sissades Tongsima
Affiliations:
Research and Development Center for Intelligent Systems, King Mongkut’s Institute of Technology North Bangkok, Bangkok, Thailand;Research and Development Center for Intelligent Systems, King Mongkut’s Institute of Technology North Bangkok, Bangkok, Thailand;National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathumthani, Thailand
Venue:
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
Year:
2006

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Abstract

This paper presents the use of an ant colony system (ACS) algorithm in DNA fragment assembly. The assembly problem generally arises during the sequencing of large strands of DNA where the strands are needed to be shotgun-replicated and broken into fragments that are small enough for sequencing. The assembly problem can thus be classified as a combinatorial optimisation problem where the aim is to find the right order of each fragment in the ordering sequence that leads to the formation of a consensus sequence that truly reflects the original DNA strands. The assembly procedure proposed is composed of two stages: fragment assembly and contiguous sequence (contig) assembly. In the fragment assembly stage, a possible alignment between fragments is determined with the use of a Smith-Waterman algorithm where the fragment ordering sequence is created using the ACS algorithm. The resulting contigs are then assembled together using a nearest neighbour heuristic (NNH) rule. The results indicate that in overall the performance of the combined ACS/NNH technique is superior to that of the NNH search and a CAP3 program. The results also reveal that the solutions produced by the CAP3 program contain a higher number of contigs than the solutions produced by the proposed technique. In addition, the quality of the combined ACS/NNH solutions is higher than that of the CAP3 solutions when the problem size is large.