Bayesian Genomic Selection

Bayesian Genomic Selection is a statistical modeling framework within genomic selection that employs Bayesian inference methods to estimate the effects of genetic markers on nutritional traits by incorporating prior distributions and updating them with observed phenotypic and genotypic data.

143

Publications

12.8K

Citations

674

Authors

262

Institutions

Publications per year

2017–2026

67

Authors

674

  1. JC
    José Crossa

    Centro Internacional de Mejoramiento de Maíz Y Trigo, Mexico

    11 publications · 1K citations

    11

    h-index

  2. RL
    Rohan L. Fernando

    Iowa State University, United States

    9 publications · 3K citations

    9

    h-index

  3. PP
    Paulino Pérez‐Rodríguez

    Colegio de Postgraduados, Mexico

    7 publications · 687 citations

    7

    h-index

  4. BJ
    Ben J. Hayes

    The University of Queensland, Australia

    7 publications · 876 citations

    7

    h-index

  5. DJ
    Dorian J. Garrick

    Massey University, New Zealand

    7 publications · 2.2K citations

    7

    h-index

1–5 of 674

Venues

  1. Genetics Selection Evolution

    GSE · 24 publications · 2.4K citations

    20

    h-index

  2. The Plant Genome

    8 publications · 887 citations

    8

    h-index

  3. Journal of Animal Science

    6 publications · 641 citations

    6

    h-index

  4. BMC Proceedings

    6 publications · 180 citations

    6

    h-index

  5. Crop Science

    5 publications · 821 citations

    5

    h-index

1–5