Partitioned Likelihood Analysis

Partitioned Likelihood Analysis is a phylogenetic inference method that employs a partitioned model structure to allow distinct subsets of sequence data to evolve under separate substitution models and parameters while jointly estimating the likelihood of a shared phylogenetic tree.

9

Publications

760

Citations

32

Authors

31

Institutions

Publications per year

2017–2026

2

Authors

32

  1. FA
    Felix A. H. Sperling

    University of Alberta, Canada

    2 publications · 190 citations

    2

    h-index

  2. MM
    May M. Kuo

    University of California, Berkeley, United States

    2 publications · 190 citations

    2

    h-index

  3. MS
    Michael S. Caterino

    Santa Barbara Museum of Natural History, United States

    2 publications · 190 citations

    2

    h-index

  4. RD
    Robert D. Reed

    Cornell University, United States

    2 publications · 190 citations

    2

    h-index

  5. MJ
    Markus J. Ankenbrand

    University of Würzburg, Germany

    1 publications · 173 citations

    1

    h-index

1–5 of 32

Venues

  1. Systematic Biology

    3 publications · 278 citations

    3

    h-index

  2. Genome

    1 publications · 173 citations

    1

    h-index

  3. Computational Statistics

    1 publications · 13 citations

    1

    h-index

  4. American Journal of Botany

    1 publications · 68 citations

    1

    h-index

  5. BMC Biology

    1 publications · 72 citations

    1

    h-index

1–5