Publication | Closed Access
Fixed-Parameter Algorithms for Maximum Agreement Forests
92
Citations
26
References
2013
Year
EngineeringMachine LearningSpeech RecognitionAgreement ForestPhylogeneticsData ScienceData MiningPattern RecognitionMolecular EcologyBiogeographyParameterized AlgorithmMaximum Agreement ForestsRobust Speech RecognitionDecision Tree LearningPhylogeny ComparisonBiodiversityKnowledge DiscoveryComputer SciencePhylogenomicsBiologyImproved Fixed-parameter AlgorithmsNatural SciencesEvolutionary BiologyPhylogenetic MethodSpeech ProcessingSymbiosis
We present new and improved fixed-parameter algorithms for computing maximum agreement forests of pairs of rooted binary phylogenetic trees. The size of such a forest for two trees corresponds to their subtree prune-and-regraft distance and, if the agreement forest is acyclic, to their hybridization number. These distance measures are essential tools for understanding reticulate evolution. Our algorithm for computing maximum acyclic agreement forests is the first depth-bounded search algorithm for this problem. Our algorithms substantially outperform the best previous algorithms for these problems.
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