A Pseudo-boolean Programming Approach for Computing the Breakpoint Distance Between Two Genomes with Duplicate Genes
Comparing genomes of different species has become a crucial problem in comparative genomics. Recent research have resulted in different genomic distance definitions: number of breakpoints, number of common intervals, number of conserved intervals, Maximum Adjacency Disruption number (MAD), etc. Classical methods (usually based on permutations of gene order) for computing genomic distances between whole genomes are however seriously compromised for genomes where several copies of the same gene may be scattered across the genome. Most approaches to overcoming this difficulty are based on the exemplar method (keep exactly one copy in each genome of each duplicated gene) and the maximum matching method (keep as many copies as possible in each genome of each duplicated gene). Unfortunately, it turns out that, in presence of duplications, most problems are NP-hard, and hence several heuristics have been recently proposed.
Extending research initiated in , we propose in this paper a novel generic pseudo-boolean approach for computing the exact breakpoint distance between two genomes in presence of duplications for both the exemplar and maximum matching methods. We illustrate the application of this methodology on a well-known public benchmark dataset of γ-Proteobacteria.
Keywordsgenome rearrangement duplication breakpoint distance heuristic pseudo-boolean programming
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