Concepedia

Genetic Covariance Function Analysis

Genetic Covariance Function Analysis is a statistical methodological framework within longitudinal genetic analysis that models the temporal dynamics of genetic effects by estimating how genetic influences on traits covary across different time points, thereby distinguishing itself from static genetic covariance approaches through its explicit modeling of time-dependent genetic variance structures.

2

Publications

31

Citations

9

Authors

2

Institutions

Publications per year

2017–2026

1

Parents

Publications

2

1–2 of 2

Authors

9

  1. PA
    P. A. Carter

    Washington State University, United States

    1 publications · 13 citations

    1

    h-index

  2. PX
    Pao Xu

    Chinese Academy of Fishery Sciences, China

    1 publications · 18 citations

    1

    h-index

  3. JH
    Jie He

    Chinese Academy of Medical Sciences & Peking Union Medical College, China

    1 publications · 18 citations

    1

    h-index

  4. JZ
    Jingli Zhao

    Chinese Academy of Fishery Sciences, China

    1 publications · 18 citations

    1

    h-index

  5. KK
    Kristen K. Irwin

    Arizona State University, United States

    1 publications · 13 citations

    1

    h-index

1–5 of 9

Institutions

2

  1. Chinese Academy of Fishery Sciences

    Beijing, China

    1 h-index

    6 publications

    108 citations

  2. Washington State University

    Pullman, United States

    1 h-index

    2 publications

    26 citations

1–2 of 2

Venues

  1. Journal of Evolutionary Biology

    JEB · 1 publications · 13 citations

    1

    h-index

  2. Genetics Selection Evolution

    GSE · 1 publications · 18 citations

    1

    h-index

1–2