Bayesian Estimation of Divergence Times From Large Sequence Alignments

Stéphane Guindon 1
1 MAB - Méthodes et Algorithmes pour la Bioinformatique
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : Bayesian estimation of divergence times from molecular sequences relies on sophisticated Markov chain Monte Carlo techniques, and Metropolis-Hastings (MH) samplers have been successfully used in that context. This approach involves heavy computational burdens that can hinder the analysis of large phylogenomic data sets. Reliable estimation of divergence times can also be extremely time consuming, if not impossible, for sequence alignments that convey weak or conflicting phylogenetic signals, ...
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Article dans une revue
Molecular Biology and Evolution, Oxford University Press (OUP), 2010, 27, pp.1768-1781
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00705189
Contributeur : Stephane Guindon <>
Soumis le : jeudi 7 juin 2012 - 09:46:10
Dernière modification le : jeudi 24 mai 2018 - 15:59:22

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Stéphane Guindon. Bayesian Estimation of Divergence Times From Large Sequence Alignments. Molecular Biology and Evolution, Oxford University Press (OUP), 2010, 27, pp.1768-1781. 〈lirmm-00705189〉

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