Motif Statistics

Motif Statistics is a computational method within network analysis that quantifies the significance of recurring subgraph patterns by comparing their observed frequencies to those expected under a specified null model.

55

Publications

2.2K

Citations

173

Authors

118

Institutions

Publications per year

2017–2026

15

Authors

173

  1. PW
    Pinghui Wang

    Xi'an Jiaotong University, China

    4 publications · 146 citations

    4

    h-index

  2. DT
    Don Towsley

    University of Massachusetts Amherst, United States

    4 publications · 146 citations

    4

    h-index

  3. JC
    John C. S. Lui

    Chinese University of Hong Kong, Hong Kong SAR China

    4 publications · 146 citations

    4

    h-index

  4. JZ
    Junzhou Zhao

    Xi'an Jiaotong University, China

    4 publications · 149 citations

    4

    h-index

  5. SS
    Sophie Schbath

    Mathématiques et Informatique Appliquées du Génome à l'Environnement, France

    3 publications · 137 citations

    3

    h-index

1–5 of 173

Venues

  1. Bioinformatics

    5 publications · 161 citations

    5

    h-index

  2. arXiv (Cornell University)

    Repository · 5 publications · 108 citations

    5

    h-index

  3. IEEE Access

    2 publications · 45 citations

    2

    h-index

  4. Scientific Reports

    2 publications · 30 citations

    2

    h-index

  5. Discrete Applied Mathematics

    2 publications · 40 citations

    2

    h-index

1–5