Genome Rearrangement Based on Reversals that Preserve Conserved Intervals
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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RECOMB-CG '08 Proceedings of the international workshop on Comparative Genomics
RECOMB-CG '08 Proceedings of the international workshop on Comparative Genomics
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RECOMB-CG '08 Proceedings of the international workshop on Comparative Genomics
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RECOMB-CG '08 Proceedings of the international workshop on Comparative Genomics
Solving the Preserving Reversal Median Problem
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
RECOMB-CG '09 Proceedings of the International Workshop on Comparative Genomics
A fast and exact algorithm for the perfect reversal median problem
ISBRA'07 Proceedings of the 3rd international conference on Bioinformatics research and applications
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RECOMB-CG'07 Proceedings of the 2007 international conference on Comparative genomics
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EvoCOP'08 Proceedings of the 8th European conference on Evolutionary computation in combinatorial optimization
WABI'09 Proceedings of the 9th international conference on Algorithms in bioinformatics
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RECOMB-CG'10 Proceedings of the 2010 international conference on Comparative genomics
The transposition median problem is NP-complete
Theoretical Computer Science
A practical algorithm for ancestral rearrangement reconstruction
WABI'11 Proceedings of the 11th international conference on Algorithms in bioinformatics
A parallel algorithm for solving the reversal median problem
PPAM'05 Proceedings of the 6th international conference on Parallel Processing and Applied Mathematics
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CompLife'06 Proceedings of the Second international conference on Computational Life Sciences
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In this paper, we study theReversal Median Problem (RMP), which arises in computational biology as a basic model for the reconstruction of evolutionary trees. Givenq genomes, RMP calls for another genome such that the sum of the reversal distances between this genome and the given ones is minimized. So far, the problem has been considered too complex to derive mathematical models useful for its analysis and solution. We provide a powerful graph-theoretic relaxation of RMP, essentially calling for a perfect matching in a graph that forms the maximum number of cycles jointly withq given perfect matchings. By using this relaxation, we can show the complexity of RMP as well as design effective algorithms for its exact and heuristic solution. We report the solution of a few hundred instances associated with real-world genomes.