Solving the Preserving Reversal Median Problem
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Finding All Sorting Tandem Duplication Random Loss Operations
CPM '09 Proceedings of the 20th Annual Symposium on Combinatorial Pattern Matching
A fast and exact algorithm for the perfect reversal median problem
ISBRA'07 Proceedings of the 3rd international conference on Bioinformatics research and applications
Improving inversion median computation using commuting reversals and cycle information
RECOMB-CG'07 Proceedings of the 2007 international conference on Comparative genomics
Reactive stochastic local search algorithms for the genomic median problem
EvoCOP'08 Proceedings of the 8th European conference on Evolutionary computation in combinatorial optimization
Finding all sorting tandem duplication random loss operations
Journal of Discrete Algorithms
A practical algorithm for ancestral rearrangement reconstruction
WABI'11 Proceedings of the 11th international conference on Algorithms in bioinformatics
Rearrangement-Based Phylogeny Using the Single-Cut-or-Join Operation
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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Motivation: Algorithms for phylogenetic tree reconstruction based on gene order data typically repeatedly solve instances of the reversal median problem (RMP) which is to find for three given gene orders a fourth gene order (called median) with a minimal sum of reversal distances. All existing algorithms of this type consider only one median for each RMP instance even when a large number of medians exist. A careful selection of one of the medians might lead to better phylogenetic trees. Results: We propose a heuristic algorithm amGRP for solving the multiple genome rearrangement problem (MGRP) by repeatedly solving instances of the RMP taking all medians into account. Algorithm amGRP uses a branch-and-bound method that branches over medians from a selected subset of all medians for each RMP instance. Different heuristics for selecting the subsets have been investigated. To show that the medians for RMP vary strongly with respect to different properties that are likely to be relevant for phylogenetic tree reconstruction, the set of all medians has been investigated for artificial datasets and mitochondrial DNA (mtDNA) gene orders. Phylogenetic trees have been computed for a large set of randomly generated gene orders and two sets of mtDNA gene order data for different animal taxa with amGRP and with two standard approaches for solving the MGRP (GRAPPA-DCM and MGR). The results show that amGRP outperforms both other methods with respect to solution quality and computation time on the test data. Availability: The source code of amGRP, additional results and the test instances used in this paper are freely available from the authors. Contact: merkle@informatik.uni-leipzig.de