Bayesian Phylogenetic Inference

Bayesian Phylogenetic Inference is a computational framework for phylogenetic inference that uses Bayesian statistics to estimate the posterior distribution of phylogenetic trees and model parameters by combining prior probabilities with the likelihood of observed sequence data under a specified evolutionary model.

1.2K

Publications

266.5K

Citations

4.5K

Authors

1.7K

Institutions

Publications per year

2017–2026

399

Authors

4.5K

  1. AJ
    Alexei J. Drummond

    University of Auckland, New Zealand

    32 publications · 57.8K citations

    28

    h-index

  2. MA
    Marc A. Suchard

    University of California, Los Angeles, United States

    38 publications · 71.9K citations

    27

    h-index

  3. JP
    John P. Huelsenbeck

    University of California, Berkeley, United States

    29 publications · 95.4K citations

    26

    h-index

  4. AR
    Andrew Rambaut

    University of Edinburgh, United Kingdom

    22 publications · 54.6K citations

    21

    h-index

  5. RB
    Remco Bouckaert

    University of Auckland, New Zealand

    23 publications · 14.1K citations

    21

    h-index

1–5 of 4.5K

Venues

  1. Systematic Biology

    148 publications · 70.5K citations

    80

    h-index

  2. Molecular Biology and Evolution

    MBE · 63 publications · 24.7K citations

    45

    h-index

  3. Molecular Phylogenetics and Evolution

    51 publications · 3.8K citations

    35

    h-index

  4. PLoS ONE

    58 publications · 2.9K citations

    31

    h-index

  5. Journal of Biogeography

    45 publications · 2.4K citations

    31

    h-index

1–5