A Simulated Annealing Algorithm for Finding Consensus Sequences
(2002) A Simulated Annealing Algorithm for Finding Consensus Sequences. Bioinformatics 18(11):pp. 1494-1499.
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Abstract
Motivation: A consensus sequence for a family of related sequences is, as the name suggests, a sequence that captures the features common to most members of the family. Consensus sequences are important in various DNA sequencing applications and are a convenient way to characterize a family of molecules. Results: This paper describes a new algorithm for finding a consensus sequence, using the popular optimization method known as simulated annealing. Unlike the conventional approach of finding a consensus sequence by first forming a multiple sequence alignment, this algorithm searches for a sequence that minimises the sum of pairwise distances to each of the input sequences. The resulting consensus sequence can then be used to induce a multiple sequence alignment. The time required by the algorithm scales linearly with the number of input sequences and quadratically with the length of the consensus sequence. We present results demonstrating the high quality of the consensus sequences and alignments produced by the new altorithm. For comparison, we also present similar results obtained using Clustal W. The new algorithm outperforms ClustalW in many cases. Availability: The software is made available upon request. Contact: jonathan@maths.uq.edu.au
| Item Type: | Journal Article |
|---|---|
| Status: | Published |
| Subjects: | 230000 Mathematical Sciences > 239900 Other Mathematical Sciences > 239901 Biological Mathematics |
| ID Code: | 8017 |
| Deposited By: | Keith, Jonathan M |
| Deposited On: | 06 June 2007 |
| Alternative Locations: | http://bioinformatics.oxfordjournals.org/ |
| Copyright Owner: | Copyright 2002 Oxford University Press |
| Additional Information: | For more information, please refer to the publisher's website (link above) or contact the author: j.keith@qut.edu.au |