Linkage Learning

Linkage Learning is a computational method in population genetics that identifies and models the non-random associations between alleles at different loci to infer historical recombination patterns within a population.

37

Publications

1.7K

Citations

66

Authors

48

Institutions

Publications per year

2017–2026

6

Authors

66

  1. DT
    Dirk Thierens

    Utrecht University, Netherlands

    5 publications · 202 citations

    5

    h-index

  2. PA
    Peter A. N. Bosman

    Centrum Wiskunde & Informatica, Netherlands

    5 publications · 199 citations

    5

    h-index

  3. DE
    David E. Goldberg

    University of Illinois Urbana-Champaign, United States

    5 publications · 205 citations

    5

    h-index

  4. MW
    Michal W. Przewozniczek

    Wrocław University of Science and Technology, Poland

    4 publications · 86 citations

    4

    h-index

  5. MM
    Marcin M. Komarnicki

    Wrocław University of Science and Technology, Poland

    3 publications · 65 citations

    3

    h-index

1–5 of 66

Venues

  1. 2

    h-index

  2. IEEE Transactions on Evolutionary Computation

    2 publications · 62 citations

    2

    h-index

  3. Journal of Computational Biology

    1 publications · 99 citations

    1

    h-index

  4. Data & Knowledge Engineering

    DKE · 1 publications · 12 citations

    1

    h-index

  5. Complexity

    1 publications · 46 citations

    1

    h-index

1–5