Expression Fold Change Analysis

Expression Fold Change Analysis is a computational method in differential expression analysis that quantifies the magnitude of change in gene expression levels between experimental conditions by calculating the ratio of expression intensities, normalized to a reference state, to identify biologically significant up- or down-regulated genes.

501

Publications

36.6K

Citations

3.1K

Authors

964

Institutions

Publications per year

2017–2026

147

Authors

3.1K

  1. EM
    Eckart Meese

    Saarland University, Germany

    3 publications · 103 citations

    3

    h-index

  2. AK
    Andreas Keller

    Saarland University, Germany

    3 publications · 103 citations

    3

    h-index

  3. MI
    Michael I. Love

    University of North Carolina at Chapel Hill, United States

    3 publications · 3.1K citations

    3

    h-index

  4. MX
    Mu Xu

    Nanjing Medical University, China

    3 publications · 332 citations

    3

    h-index

  5. VB
    Vikram Budhraja

    Washington University in St. Louis, United States

    2 publications · 163 citations

    2

    h-index

1–5 of 3.1K

Venues

  1. PLoS ONE

    43 publications · 2.4K citations

    28

    h-index

  2. BMC Bioinformatics

    19 publications · 2K citations

    17

    h-index

  3. BMC Genomics

    17 publications · 620 citations

    16

    h-index

  4. Bioinformatics

    15 publications · 4.6K citations

    15

    h-index

  5. Scientific Reports

    17 publications · 821 citations

    14

    h-index

1–5