Improving the accuracy of demographic and molecular clock model comparison while accommodating phylogenetic uncertainty.

By Guy Baele, Philippe Lemey, Trevor Bedford, Andrew Rambaut, Marc A. Suchard, A. Alekseyenko. Molecular biology and evolution, 2012

1,101 citations recorded by the source corpus.

Subfields: Genetics, Molecular Biology, Paleontology

View Paper: https://www.semanticscholar.org/paper/6e05bafdb23a2b4554768c46c677159227c00cba

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Citations in the corpus

BEAST 2: A Software Platform for Bayesian Evolutionary Analysis (2014, methodology): “BEAST2 can also be made to perform Metropolis-coupled MCMC and the path sampling approach to model comparison [12] is also implemented.”
Accurate model selection of relaxed molecular clocks in bayesian phylogenetics. (2012, methodology): “For more detailed information on these methods and the way they are implemented in BEAST (Drummond et al. 2012), we refer interested readers to Baele et al. (2012).”
Population Demography and Genetic Diversity in the Pleistocene Cave Lion (2015, background): “models (Baele et al., 2012; Baele et al., 2013).”
Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10 (2018, methodology): “BEAST 1.10 now features marginal likelihood estimation (Baele et al. 2012), using path sampling (Gelman and Meng 1998; Lartillot and Philippe 2006) and stepping-stone sampling (Xie et al. 2011), as well as the recently developed generalized stepping-stone sampling (Fan et al. 2011; Baele et al.…”
The peril of dating beetles (2017, background): “…of dating programs such as beast (Drummond et al., 2012) incorporate means to estimate these marginal likelihoods in a more sensitive and sound way than before (Baele et al., 2012), thereby improving the robustness of the statistical framework in which comparative dating analyses are conducted.”
In and out of the Qinghai‐Tibet Plateau: divergence time estimation and historical biogeography of the large arctic‐alpine genus Saxifraga L. (2017, methodology): “Bayesian model selection was performed using the posterior simulation-based analogue of Akaike information criterion through Markov chain Monte Carlo (AICM; Baele et al., 2012) implemented in Tracer 1.6.”
Species Delimitation using Genome-Wide SNP Data (2013, methodology): “In addition, marginal likelihoods provide a convenient way to rank alternative, even non-nested, models with the advantage of automatic model complexity penalization Baele et al. (2012).”