Gene Co-expression Analysis

Gene Co-Expression Analysis is a computational method in gene expression analysis that identifies pairs or groups of genes exhibiting similar expression patterns across multiple conditions or samples, thereby inferring functional associations or regulatory relationships based on coordinated transcriptional activity.

1.7K

Publications

149.5K

Citations

8.6K

Authors

2K

Institutions

Publications per year

2017–2026

938

Authors

8.6K

  1. SH
    Steve Horvath

    University of California, Los Angeles, United States

    19 publications · 39.1K citations

    19

    h-index

  2. KH
    Kun Huang

    The Ohio State University, United States

    12 publications · 436 citations

    11

    h-index

  3. PL
    Peter Langfelder

    University of California, Los Angeles, United States

    9 publications · 32K citations

    9

    h-index

  4. ZZ
    Zhongming Zhao

    The University of Texas Health Science Center at Houston, United States

    9 publications · 574 citations

    9

    h-index

  5. YX
    Yu Xiao

    Wuhan University, China

    8 publications · 507 citations

    8

    h-index

1–5 of 8.6K

Venues

  1. Bioinformatics

    115 publications · 12.6K citations

    55

    h-index

  2. BMC Bioinformatics

    103 publications · 38.4K citations

    42

    h-index

  3. Nucleic Acids Research

    71 publications · 5.9K citations

    39

    h-index

  4. PLoS ONE

    85 publications · 3.9K citations

    35

    h-index

  5. BMC Genomics

    65 publications · 3.5K citations

    33

    h-index

1–5