Sampling Bias Correction

Sampling Bias Correction is a methodological framework in genomic epidemiology that adjusts for systematic distortions in observed data arising from non-random sampling processes, thereby enabling more accurate inference of evolutionary dynamics, last appearance datums, or pathogen burden estimates such as tonnage.

151

Publications

14.9K

Citations

882

Authors

404

Institutions

Publications per year

2017–2026

54

Authors

882

  1. DF
    Dejian Fu

    Jet Propulsion Laboratory, United States

    2 publications · 123 citations

    2

    h-index

  2. ND
    Nicola De Maio

    European Bioinformatics Institute, United Kingdom

    2 publications · 73 citations

    2

    h-index

  3. TM
    Tim Morris

    University of Bristol, United Kingdom

    2 publications · 1.1K citations

    2

    h-index

  4. BF
    B. Fisher

    Jet Propulsion Laboratory, United States

    2 publications · 123 citations

    2

    h-index

  5. LZ
    Luisa Zuccolo

    University of Bristol, United Kingdom

    2 publications · 1.1K citations

    2

    h-index

1–5 of 882

Venues

  1. Methods in Ecology and Evolution

    5 publications · 761 citations

    5

    h-index

  2. Ecography

    4 publications · 335 citations

    4

    h-index

  3. Ecological Informatics

    4 publications · 110 citations

    4

    h-index

  4. PubMed

    Repository · 4 publications · 125 citations

    4

    h-index

  5. Biometrics

    4 publications · 170 citations

    4

    h-index

1–5