Causal Network Inference

Causal Network Inference is a computational framework within network inference that specifically identifies directed regulatory relationships among variables by distinguishing direct causal interactions from mere correlations through the application of probabilistic, interventional, or temporal modeling principles.

364

Publications

33.3K

Citations

1.4K

Authors

663

Institutions

Publications per year

2017–2026

176

Authors

1.4K

  1. CY
    Changwon Yoo

    Florida International University, United States

    4 publications · 229 citations

    4

    h-index

  2. DZ
    Daniel Ziemek

    Pfizer (United States), United States

    4 publications · 207 citations

    4

    h-index

  3. GF
    Gregory F. Cooper

    University of Pittsburgh, United States

    4 publications · 257 citations

    4

    h-index

  4. SM
    Sach Mukherjee

    University of Warwick, United Kingdom

    4 publications · 367 citations

    4

    h-index

  5. AE
    Ahmed Enayetallah

    Pfizer (United States), United States

    3 publications · 166 citations

    3

    h-index

1–5 of 1.4K

Venues

  1. Bioinformatics

    17 publications · 7.7K citations

    15

    h-index

  2. PLoS ONE

    16 publications · 454 citations

    14

    h-index

  3. arXiv (Cornell University)

    Repository · 11 publications · 364 citations

    11

    h-index

  4. BMC Bioinformatics

    6 publications · 265 citations

    6

    h-index

  5. 6

    h-index

1–5