Module Detection Algorithms

Module Detection Algorithms is a computational method that identifies densely connected subgroups within complex networks by optimizing partitioning criteria to distinguish modular structures from random connectivity patterns.

166

Publications

34.1K

Citations

490

Authors

305

Institutions

Publications per year

2017–2026

58

Variants

Community Detection Algorithms

Authors

490

  1. AZ
    Aidong Zhang

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

    7 publications · 434 citations

    7

    h-index

  2. YC
    Young‐Rae Cho

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

    4 publications · 287 citations

    4

    h-index

  3. ME
    M. E. J. Newman

    University of Michigan, United States

    3 publications · 18.3K citations

    3

    h-index

  4. JJ
    Junzhong Ji

    Beijing University of Technology, China

    3 publications · 129 citations

    3

    h-index

  5. LG
    Lin Gao

    Xidian University, China

    3 publications · 108 citations

    3

    h-index

1–5 of 490

Venues

  1. Physical Review E

    PRE · 9 publications · 7.3K citations

    9

    h-index

  2. BMC Bioinformatics

    8 publications · 344 citations

    8

    h-index

  3. Scientific Reports

    8 publications · 597 citations

    8

    h-index

  4. Information Sciences

    6 publications · 290 citations

    6

    h-index

  5. PLoS ONE

    4 publications · 392 citations

    4

    h-index

1–5