Selective Sweep Detection

Selective Sweep Detection is a computational inference method in population genetics that identifies genomic regions under recent positive selection by distinguishing the signature of reduced genetic variation caused by the rapid fixation of beneficial alleles from neutral evolutionary processes.

80

Publications

10.1K

Citations

341

Authors

162

Institutions

Publications per year

2017–2026

32

Authors

341

  1. DR
    Daniel R. Schrider

    University of North Carolina at Chapel Hill, United States

    7 publications · 570 citations

    6

    h-index

  2. MD
    Michael DeGiorgio

    Pennsylvania State University, United States

    6 publications · 464 citations

    6

    h-index

  3. AD
    Andrew D. Kern

    University of Oregon, United States

    6 publications · 541 citations

    5

    h-index

  4. NA
    Nikolaos Alachiotis

    Foundation for Research and Technology Hellas, Greece

    5 publications · 970 citations

    5

    h-index

  5. ZA
    Zachary A. Szpiech

    University of California, San Francisco, United States

    5 publications · 257 citations

    5

    h-index

1–5 of 341

Venues

  1. Genetics

    14 publications · 1.9K citations

    14

    h-index

  2. Molecular Biology and Evolution

    MBE · 8 publications · 1.2K citations

    8

    h-index

  3. PLoS Genetics

    5 publications · 968 citations

    5

    h-index

  4. Genome Research

    GR · 4 publications · 2.3K citations

    4

    h-index

  5. BMC Genomics

    4 publications · 205 citations

    4

    h-index

1–5