Pedigree Graph Modeling

Pedigree Graph Modeling is a formal computational framework that represents familial relationships and genetic inheritance patterns as a directed acyclic graph, where nodes denote individuals and edges encode parent-offspring lineage to enable structured integration and analysis of pedigree data.

10

Publications

1.9K

Citations

24

Authors

17

Institutions

Publications per year

2017–2026

0

Authors

24

  1. MH
    Mark H. Skolnick

    University of Utah, United States

    2 publications · 455 citations

    2

    h-index

  2. EA
    E. A. Thompson

    University of Washington, United States

    2 publications · 455 citations

    2

    h-index

  3. CC
    C. Cannings

    University of Sheffield, United Kingdom

    2 publications · 455 citations

    2

    h-index

  4. CJ
    Claus Jensen

    Department of Agricultural Sciences, Russia

    1 publications · 80 citations

    1

    h-index

  5. KL
    Kenneth Lange

    University of California, Los Angeles, United States

    1 publications · 1.2K citations

    1

    h-index

1–5 of 24

Venues

  1. PubMed

    Repository · 2 publications · 1.2K citations

    2

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  2. Advances in Applied Probability

    AAP · 2 publications · 455 citations

    2

    h-index

  3. Theoretical Population Biology

    TPB · 1 publications · 13 citations

    1

    h-index

  4. Bioinformatics

    1 publications · 23 citations

    1

    h-index

  5. Heredity

    1 publications · 34 citations

    1

    h-index

1–5