Statistical Analysis Of Differential Expression

Statistical Analysis of Differential Expression is a quantitative methodological framework in proteomics that belongs to the class of statistical inference techniques, specifically designed to identify and quantify significant changes in protein abundance across biological conditions while controlling for experimental variability and false discovery rates.

376

Publications

91.8K

Citations

1.3K

Authors

506

Institutions

Publications per year

2017–2026

49

Authors

1.3K

  1. GK
    Gordon K. Smyth

    Walter and Eliza Hall Institute of Medical Research, Australia

    6 publications · 47.4K citations

    6

    h-index

  2. NA
    Natasha A. Karp

    Wellcome Sanger Institute, United Kingdom

    5 publications · 751 citations

    5

    h-index

  3. RB
    Rainer Breitling

    University of Groningen, Netherlands

    5 publications · 2.6K citations

    5

    h-index

  4. MI
    Michael I. Love

    University of North Carolina at Chapel Hill, United States

    5 publications · 2.9K citations

    5

    h-index

  5. NT
    Norman T. J. Bailey

    University of Cambridge, United Kingdom

    5 publications · 1.1K citations

    5

    h-index

1–5 of 1.3K

Venues

  1. Bioinformatics

    68 publications · 59.1K citations

    40

    h-index

  2. BMC Bioinformatics

    34 publications · 1.8K citations

    23

    h-index

  3. Journal of Proteome Research

    JPR · 18 publications · 1.8K citations

    15

    h-index

  4. Statistical Applications in Genetics and Molecular Biology

    SAGMB · 14 publications · 1.3K citations

    12

    h-index

  5. PROTEOMICS

    11 publications · 748 citations

    11

    h-index

1–5