Missing Interaction Imputation

Missing Interaction Imputation is a computational method within protein-protein interaction network analysis that infers unobserved or experimentally undetected interactions by leveraging topological, functional, or evolutionary patterns in the network to distinguish likely true interactions from missing data.

26

Publications

2.1K

Citations

90

Authors

60

Institutions

Publications per year

2017–2026

9

Authors

90

  1. MW
    Mengyun Wu

    Shanghai University of Finance and Economics, China

    3 publications · 47 citations

    3

    h-index

  2. MV
    Marc Vidal

    Dana-Farber Cancer Institute, United States

    2 publications · 524 citations

    2

    h-index

  3. GC
    Gholamali C. Shoja

    University of Victoria, Canada

    2 publications · 41 citations

    2

    h-index

  4. CP
    Carl Pollis

    Dana-Farber Cancer Institute, United States

    2 publications · 524 citations

    2

    h-index

  5. TH
    Tong Hao

    Harvard University, United States

    2 publications · 524 citations

    2

    h-index

1–5 of 90

Venues

  1. Bioinformatics

    3 publications · 92 citations

    3

    h-index

  2. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 2 publications · 236 citations

    2

    h-index

  3. Statistics in Medicine

    2 publications · 120 citations

    2

    h-index

  4. Social Networks

    1 publications · 17 citations

    1

    h-index

  5. BMC Bioinformatics

    1 publications · 25 citations

    1

    h-index

1–5