Kernel-based Genomic Prediction

Kernel-Based Genomic Prediction is a genomic prediction method that employs kernel functions to model nonlinear relationships between genotypes and phenotypes by mapping genetic marker data into a higher-dimensional space where pairwise similarities are quantified to improve predictive accuracy across environments.

47

Publications

4.7K

Citations

240

Authors

111

Institutions

Publications per year

2017–2026

31

Authors

240

  1. JC
    José Crossa

    Centro Internacional de Mejoramiento de Maíz Y Trigo, Mexico

    10 publications · 1.1K citations

    10

    h-index

  2. JC
    Jaime Cuevas

    University of Quintana Roo, Mexico

    6 publications · 562 citations

    6

    h-index

  3. OA
    Osval A. Montesinos‐López

    Universidad de Colima, Mexico

    6 publications · 459 citations

    6

    h-index

  4. PP
    Paulino Pérez‐Rodríguez

    Colegio de Postgraduados, Mexico

    5 publications · 515 citations

    5

    h-index

  5. RF
    Roberto Fritsche‐Neto

    Universidade de São Paulo, Brazil

    4 publications · 361 citations

    4

    h-index

1–5 of 240

Venues

  1. Frontiers in Genetics

    6 publications · 301 citations

    6

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  2. G3 Genes Genomes Genetics

    5 publications · 311 citations

    5

    h-index

  3. BMC Bioinformatics

    3 publications · 82 citations

    3

    h-index

  4. The Plant Genome

    3 publications · 2.4K citations

    3

    h-index

  5. Briefings in Bioinformatics

    1 publications · 41 citations

    2

    h-index

1–5