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Nucleic Acids Research Advance Access originally published online on April 29, 2008
Nucleic Acids Research 2008 36(10):3455-3462; doi:10.1093/nar/gkn168
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Nucleic Acids Research, 2008, Vol. 36, No. 10 3455-3462
© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Computational Biology

A new pheromone trail-based genetic algorithm for comparative genome assembly

Fangqing Zhao1, Fanggeng Zhao2, Tao Li1 and Donald A. Bryant1,*

1Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, 16802, USA and 2Institute of Vehicle Management, Bengbu, 233011, China

*To whom correspondence should be addressed. Tel: +1 814 865 1992; Fax: +1 814 863 7024; Email: dab14{at}psu.edu

Received November 29, 2007. Revised February 28, 2008. Accepted March 24, 2008.

Gap closing is considered one of the most challenging and time-consuming tasks in bacterial genome sequencing projects, especially with the emergence of new sequencing technologies, such as pyrosequencing, which may result in large amounts of data without the benefit of large insert libraries for contig scaffolding. We propose a novel algorithm to align contigs with more than one reference genome at a time. This approach can successfully overcome the limitations of low degrees of conserved gene order for the reference and target genomes. A pheromone trail-based genetic algorithm (PGA) was used to search globally for the optimal placement for each contig. Extensive testing on simulated and real data sets shows that PGA significantly outperforms previous methods, especially when assembling genomes that are only moderately related. An extended version of PGA can predict additional candidate connections for each contig and can thus increase the likelihood of identifying the correct arrangement of each contig. The software and test data sets can be accessed at http://sourceforge.net/projects/pga4genomics/.


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