Directed Network Inference

Directed Network Inference is a computational methodology within network inference that specifically aims to reconstruct asymmetric relationships between variables by identifying the directionality of interactions, distinguishing it from undirected or symmetric network reconstruction approaches.

38

Publications

1.7K

Citations

119

Authors

91

Institutions

Publications per year

2017–2026

18

Authors

119

  1. YS
    Yanning Shen

    University of Minnesota, United States

    3 publications · 171 citations

    3

    h-index

  2. GB
    Georgios B. Giannakis

    University of Minnesota, United States

    3 publications · 171 citations

    3

    h-index

  3. JW
    Jianmin Wang

    Tsinghua University, China

    2 publications · 28 citations

    2

    h-index

  4. CL
    Chenlei Leng

    National University of Singapore, Singapore

    2 publications · 104 citations

    2

    h-index

  5. SE
    Stephen E. Fienberg

    Carnegie Mellon University, United States

    2 publications · 104 citations

    2

    h-index

1–5 of 119

Venues

  1. Bioinformatics

    3 publications · 106 citations

    3

    h-index

  2. IEEE Transactions on Signal Processing

    2 publications · 147 citations

    2

    h-index

  3. 2

    h-index

  4. 1

    h-index

  5. Computational Biology and Chemistry

    CBAC · 1 publications · 11 citations

    1

    h-index

1–5