DCA: An efficient implementation of the divide-and-conquer approach to simultaneous multiple sequence alignment

New Zealand Journal of Agricultural Research

2007

Obtaining an accurate multiple alignment of protein sequences is a difficult computational problem for which many heuristic techniques sacrifice optimality to achieve reasonable running time. The algorithm in this paper solves the multiple sequence alignment in three steps. Firstly, a divide-and-conquer strategy based on the genetic algorithm is used to divide the set of sequences into several subsections vertically. Secondly, a multiple sequence alignment approach based on the ant colony algorithm is used for sequences of each subsection. Finally, the alignment of original sequences can be obtained by assembling the result of each subsection. The local optimality of ant colony algorithm is prevented by combining global updating and local updating the pheromone and by adjusting the parameters adaptively. The divide-and-conquer technique helps to improve the quality of solution greatly and to reduce the running time. It has been A07070; Online publication date 17 December 2007Received and accepted 10 August 2007 shown experimentally that the algorithm is efficient formultiple sequence alignment problem.

Section: -G Rrr S Vg Wc Avs K P E a T Kc Fcwqrkmrxvr G ? Pv S C Lxrdmentioning

confidence: 99%

An efficient algorithm for multiple sequence alignment based on ant colony optimisation and divide‐and‐conquer method

Wei

Ling

New Zealand Journal of Agricultural Research

2007

“…Stoye described a new divide and conquer algorithm DCA [4] sits on top of MSA and expands its capabilities. Recently, OMA, an iterative implementation of DCA [5] is proposed to speed up the DCA strategy and reduce memory requirements.…”

Section: Introductionmentioning

confidence: 99%

Multiple Sequence Alignment by Ant Colony Optimization and Divide-and-Conquer

Pan

Computational Science – ICCS 2006

et al. 2006

Abstract.Multiple sequence alignment is a common task in molecular biology and bioinformatics. Obtaining an accurate alignment of protein sequences is a difficult computational problem because many heuristic techniques cannot achieve optimality in a reasonable running time. A novel multiple sequence alignment algorithm based on ant colony optimization and divide-and-conquer technique is proposed. The algorithm divides a set of sequences into several subsections vertically by bisecting the sequences recursively using the ant colony optimization method. We also present two methods that adaptively adjust the parameters and update the pheromones to avoid local optimal traps. Experimental results show that the algorithm can achieve high quality solution and significantly reduce the running time.

Proceedings 16th International Parallel and Distributed Processing Symposium

“…A first step in the study of molecular biology is to analyze gene and protein sequences. When a new sequence is discovered, it is important to search sequence databases to find homologous sequences [1], and analyze structural and functional similarities and differences among multiple sequences [9,11,16].…”

Section: Introductionmentioning

confidence: 99%

“…A large number of methods have been developed for fast and accurate multiple sequence alignments. Several research projects have focused on the development of heuristics [9,11,13,16,17], and the parallel implementations of MSA algorithms [12,18].…”

Section: Introductionmentioning

confidence: 99%

Improving performance of multiple sequence alignment analysis in multi-client environments

Çatalyürek

Stahlberg

Ferreira

et al. 2002