Motif Generation

Motif Generation is a generative pattern design method that systematically produces structurally distinct, recurring subgraph patterns in a network through rule-based or algorithmic differentiation from other pattern generation techniques.

33

Publications

2K

Citations

145

Authors

61

Institutions

Publications per year

2017–2026

10

Authors

145

  1. SZ
    Songwei Zhang

    City University of Hong Kong, Hong Kong SAR China

    1 publications · 24 citations

    1

    h-index

  2. WW
    Wei-Sheng Wu

    University of Michigan, United States

    1 publications · 18 citations

    1

    h-index

  3. LL
    L.A. Litzau

    University of Minnesota, United States

    1 publications · 52 citations

    1

    h-index

  4. EE
    Eran Eden

    Technion – Israel Institute of Technology, Israel

    1 publications · 759 citations

    1

    h-index

  5. SM
    S M Colón

    Cytel (United States), United States

    1 publications · 150 citations

    1

    h-index

1–5 of 145

Venues

  1. Nucleic Acids Research

    4 publications · 256 citations

    4

    h-index

  2. Bioinformatics

    2 publications · 44 citations

    2

    h-index

  3. 2

    h-index

  4. Computer applications in the biosciences

    CABIOS · 1 publications · 25 citations

    1

    h-index

  5. IEEE Antennas and Wireless Propagation Letters

    AWPL · 1 publications · 28 citations

    1

    h-index

1–5