Normalization Of Transcriptome Data

Normalization of Transcriptome Data is a computational procedure in comparative transcriptomics that adjusts raw gene expression measurements to correct for technical variations, thereby enabling valid comparisons of transcript abundance across samples by eliminating non-biological differences such as sequencing depth or library preparation bias.

372

Publications

47.4K

Citations

1.9K

Authors

738

Institutions

Publications per year

2017–2026

144

Variants

Transcriptome Data Normalization

Authors

1.9K

  1. TP
    Terence P. Speed

    Walter and Eliza Hall Institute of Medical Research, Australia

    6 publications · 3.1K citations

    6

    h-index

  2. SD
    Sandrine Dudoit

    University of California, Berkeley, United States

    5 publications · 5.5K citations

    5

    h-index

  3. DR
    Davide Risso

    University of California, Berkeley, United States

    5 publications · 3.4K citations

    5

    h-index

  4. LC
    Lixin Cheng

    Chinese University of Hong Kong, Hong Kong SAR China

    4 publications · 181 citations

    4

    h-index

  5. KK
    Koji Kadota

    The University of Tokyo, Japan

    4 publications · 920 citations

    4

    h-index

1–5 of 1.9K

Venues

  1. PLoS ONE

    33 publications · 3.5K citations

    25

    h-index

  2. BMC Bioinformatics

    31 publications · 5.2K citations

    23

    h-index

  3. Nucleic Acids Research

    17 publications · 1.5K citations

    16

    h-index

  4. Bioinformatics

    17 publications · 2.4K citations

    16

    h-index

  5. BMC Genomics

    16 publications · 1.9K citations

    16

    h-index

1–5