Sparse Multi-trait Models

Sparse Multi-Trait Models is a statistical modeling framework in quantitative genetics that integrates multiple traits into a single predictive model while enforcing sparsity in the estimated genetic effects to identify a subset of relevant traits and markers contributing to complex phenotypes.

8

Publications

308

Citations

55

Authors

29

Institutions

Publications per year

2017–2026

4

Authors

55

  1. MK
    Mingon Kang

    Kennesaw State University, United States

    1 publications · 11 citations

    1

    h-index

  2. OA
    Osval A. Montesinos‐López

    Universidad de Colima, Mexico

    1 publications · 19 citations

    1

    h-index

  3. AM
    Abelardo Montesinos‐López

    Universidad de Colima, Mexico

    1 publications · 19 citations

    1

    h-index

  4. TK
    Teja Kattenborn

    Karlsruhe Institute of Technology, Germany

    1 publications · 77 citations

    1

    h-index

  5. AS
    Andrew S. Ross

    Virginia Mason Medical Center, United States

    1 publications · 31 citations

    1

    h-index

1–5 of 55

Venues

  1. The Plant Genome

    1 publications · 31 citations

    1

    h-index

  2. Bioinformatics

    1 publications · 66 citations

    1

    h-index

  3. Journal of Dairy Science

    JDS · 1 publications · 17 citations

    1

    h-index

  4. Genes

    1 publications · 19 citations

    1

    h-index

  5. Remote Sensing of Environment

    1 publications · 77 citations

    1

    h-index

1–5