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- W1506580433 abstract "Conventional phylogenetic tree estimation methods assume that all sites ina DNA multiple alignment have the same evolutionary history. This assumption is violated in data sets from certain bacteria and viruses due to recombination, a processthat leads to the creation of mosaic sequences from different strains and, if undetected,causes systematic errors in phylogenetic tree estimation. In the current work, a hiddenMarkov model (HMM) is employed to detect recombination events in multiple DNAsequence alignments. The emission probabilities in a given state are determined bythe branching order (topology) and the branch lengths of the respective phylogenetictree, while the transition probabilities depend on the global frequency of recombination. All model parameters are optimized in a maximum likelihood sense with the expectation maximization (EM) algorithm. The resulting parameter optimization schemeis applied to a synthetic benchmark problem and to real DNA sequences from the argFgene of four strains of the bacterium Neisseria. In both cases we find a significant im-provement over an earlier heuristic parameter estimation approach." @default.
- W1506580433 created "2016-06-24" @default.
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- W1506580433 date "2000-01-01" @default.
- W1506580433 modified "2023-09-23" @default.
- W1506580433 title "Detecting Sporadic Recombination in DNA Alignments with Hidden Markov Models." @default.
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