Bayesian Rate Estimation

Bayesian Rate Estimation is a statistical inference method that uses Bayesian probability to estimate evolutionary rates by integrating prior knowledge with observed molecular sequence data to compute posterior distributions of rate parameters.

43

Publications

4.3K

Citations

211

Authors

150

Institutions

Publications per year

2017–2026

13

Authors

211

  1. MM
    Mélodie Monod

    Imperial College London, United Kingdom

    2 publications · 72 citations

    2

    h-index

  2. AK
    Aino K. Takala

    Institute for Molecular Medicine Finland, Finland

    2 publications · 96 citations

    2

    h-index

  3. LM
    Luciana Mendes Santos Servo

    Institute of Applied Economic Research, Brazil

    2 publications · 72 citations

    2

    h-index

  4. EA
    Elja Arjas

    University of Helsinki, Finland

    2 publications · 96 citations

    2

    h-index

  5. MD
    Mario dos Reis

    University College London, United Kingdom

    2 publications · 154 citations

    2

    h-index

1–5 of 211

Venues

  1. Genetics

    3 publications · 232 citations

    3

    h-index

  2. Bioinformatics

    2 publications · 29 citations

    2

    h-index

  3. 2

    h-index

  4. Molecular Biology and Evolution

    MBE · 2 publications · 1.8K citations

    2

    h-index

  5. PLoS Computational Biology

    2 publications · 33 citations

    2

    h-index

1–5