BEAST 2 is a cross-platform program for Bayesian phylogenetic analysis of molecular sequences. It estimates rooted, time-measured phylogenies using strict or relaxed molecular clock models. It can be used as a method of reconstructing phylogenies but is also a framework for testing evolutionary hypotheses without conditioning on a single tree topology. BEAST 2 uses Markov chain Monte Carlo (MCMC) to average over tree space, so that each tree is weighted proportional to its posterior probability. BEAST 2 includes a graphical user-interface for setting up standard analyses and a suit of programs for analysing the results.

References in zbMATH (referenced in 53 articles , 1 standard article )

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  1. Bastide, Paul; Ho, Lam Si Tung; Baele, Guy; Lemey, Philippe; Suchard, Marc A.: Efficient Bayesian inference of general Gaussian models on large phylogenetic trees (2021)
  2. Bouckaert, Remco; Fischer, Mareike; Wicke, Kristina: Combinatorial perspectives on Dollo-(k) characters in phylogenetics (2021)
  3. Collienne, Lena; Elmes, Kieran; Fischer, Mareike; Bryant, David; Gavryushkin, Alex: Discrete coalescent trees (2021)
  4. Collienne, Lena; Gavryushkin, Alex: Computing nearest neighbour interchange distances between ranked phylogenetic trees (2021)
  5. Nguyen-Van-Yen, Benjamin; Del Moral, Pierre; Cazelles, Bernard: Stochastic epidemic models inference and diagnosis with Poisson random measure data augmentation (2021)
  6. Richards, Andrew; Kubatko, Laura: Bayesian-weighted triplet and quartet methods for species tree inference (2021)
  7. Borges, Rui; Kosiol, Carolin: Consistency and identifiability of the polymorphism-aware phylogenetic models (2020)
  8. Cappello, Lorenzo; Palacios, Julia A.: Sequential importance sampling for multiresolution Kingman-Tajima coalescent counting (2020)
  9. Everitt, Richard G.; Culliford, Richard; Medina-Aguayo, Felipe; Wilson, Daniel J.: Sequential Monte Carlo with transformations (2020)
  10. Ostash, Bohdan; Anisimova, Maria: Visualizing codon usage within and across genomes: concepts and tools (2020)
  11. Spade, David A.: Geometric ergodicity of a Metropolis-Hastings algorithm for Bayesian inference of phylogenetic branch lengths (2020)
  12. Spade, David A.: An extended model for phylogenetic maximum likelihood based on discrete morphological characters (2020)
  13. Wakeley, John: Developments in coalescent theory from single loci to chromosomes (2020)
  14. Grindstaff, Gillian; Owen, Megan: Representations of partial leaf sets in phylogenetic tree space (2019)
  15. Johndrow, James E.; Palacios, Julia A.: Exact limits of inference in coalescent models (2019)
  16. Keefe, Matthew J.; Ferreira, Marco A. R.; Franck, Christopher T.: Objective Bayesian analysis for Gaussian hierarchical models with intrinsic conditional autoregressive priors (2019)
  17. Warnow, Tandy (ed.): Bioinformatics and phylogenetics. Seminal contributions of Bernard Moret (2019)
  18. Bartoszek, Krzysztof: Exact and approximate limit behaviour of the Yule tree’s cophenetic index (2018)
  19. Kendall, Michelle; Ayabina, Diepreye; Xu, Yuanwei; Stimson, James; Colijn, Caroline: Estimating transmission from genetic and epidemiological data: a metric to compare transmission trees (2018)
  20. Stadler, Tanja; Gavryushkina, Alexandra; Warnock, Rachel C. M.; Drummond, Alexei J.; Heath, Tracy A.: The fossilized birth-death model for the analysis of stratigraphic range data under different speciation modes (2018)

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