Correlation-based Co-expression Analysis

Correlation-Based Co-Expression Analysis is a gene co-expression analysis method that identifies functionally related genes by quantifying pairwise transcriptional similarity using correlation coefficients, such as Pearson or Spearman, to measure the strength and direction of their expression relationships across biological samples.

42

Publications

3.7K

Citations

230

Authors

124

Institutions

Publications per year

2017–2026

12

Authors

230

  1. RK
    Rajat K. De

    Indian Statistical Institute, India

    2 publications · 66 citations

    2

    h-index

  2. AR
    Antônio Reverter

    Commonwealth Scientific and Industrial Research Organisation, Australia

    2 publications · 449 citations

    2

    h-index

  3. AB
    Anindya Bhattacharya

    Janssen (United States), United States

    2 publications · 66 citations

    2

    h-index

  4. IM
    Ioannis Michalopoulos

    Academy of Athens, Greece

    2 publications · 101 citations

    2

    h-index

  5. FL
    Fangda Li

    Chinese Academy of Medical Sciences & Peking Union Medical College, China

    1 publications · 10 citations

    1

    h-index

1–5 of 230

Venues

  1. BMC Bioinformatics

    5 publications · 549 citations

    5

    h-index

  2. Bioinformatics

    4 publications · 561 citations

    4

    h-index

  3. BMC Genomics

    3 publications · 115 citations

    3

    h-index

  4. Nucleic Acids Research

    3 publications · 101 citations

    3

    h-index

  5. PLoS ONE

    3 publications · 98 citations

    3

    h-index

1–5