Graph-based Inference

Graph-Based Inference is a computational approach within drug repurposing informatics that leverages graph-structured representations of biological and pharmacological data to identify novel therapeutic indications by systematically propagating and inferring relationships among drugs, targets, diseases, and other biomedical entities.

181

Publications

9.5K

Citations

764

Authors

323

Institutions

Publications per year

2017–2026

125

Authors

764

  1. CE
    Carey E. Priebe

    Johns Hopkins University, United States

    6 publications · 142 citations

    6

    h-index

  2. JT
    Joshua T Vogelstein

    Johns Hopkins University, United States

    5 publications · 115 citations

    5

    h-index

  3. AA
    Avanti Athreya

    Johns Hopkins University, United States

    4 publications · 111 citations

    4

    h-index

  4. MT
    Minh Tang

    Johns Hopkins University, United States

    3 publications · 61 citations

    3

    h-index

  5. SK
    Samuel Kaski

    Aalto University, Finland

    3 publications · 117 citations

    3

    h-index

1–5 of 764

Venues

  1. arXiv (Cornell University)

    Repository · 21 publications · 520 citations

    14

    h-index

  2. Bioinformatics

    5 publications · 182 citations

    5

    h-index

  3. Knowledge-Based Systems

    5 publications · 159 citations

    5

    h-index

  4. Journal of Biomedical Informatics

    4 publications · 164 citations

    4

    h-index

  5. 4

    h-index

1–5