Module Detection

Module Detection is a computational method in gene coexpression network analysis that identifies densely interconnected groups of genes, or modules, based on their expression similarity patterns across conditions, distinguishing it from general clustering techniques by incorporating network topology and biological coherence as criteria for module identification.

353

Publications

52.2K

Citations

1.4K

Authors

606

Institutions

Publications per year

2017–2026

160

Authors

1.4K

  1. AZ
    Aidong Zhang

    University at Buffalo, State University of New York, United States

    6 publications · 421 citations

    6

    h-index

  2. KH
    Kun Huang

    The Ohio State University, United States

    5 publications · 114 citations

    5

    h-index

  3. SM
    Saurav Mallik

    Harvard University, United States

    4 publications · 88 citations

    4

    h-index

  4. JZ
    Jie Zhang

    Indiana University – Purdue University Indianapolis, United States

    4 publications · 57 citations

    4

    h-index

  5. JX
    Jianhua Xuan

    Virginia Tech, United States

    4 publications · 70 citations

    4

    h-index

1–5 of 1.4K

Venues

  1. Bioinformatics

    29 publications · 2.3K citations

    24

    h-index

  2. BMC Bioinformatics

    26 publications · 30.4K citations

    17

    h-index

  3. Scientific Reports

    19 publications · 722 citations

    16

    h-index

  4. 13

    h-index

  5. PLoS ONE

    14 publications · 605 citations

    11

    h-index

1–5