Graph-based Function Prediction

Graph-Based Function Prediction is a computational method that leverages the topological structure of biological networks represented as graphs to infer the biological functions of unannotated nodes based on the annotated functions of their network neighbors.

69

Publications

5.6K

Citations

238

Authors

146

Institutions

Publications per year

2017–2026

29

Authors

238

  1. QM
    Quaid Morris

    University of Toronto, Canada

    3 publications · 445 citations

    3

    h-index

  2. GV
    Giorgio Valentini

    University of Milan, Italy

    3 publications · 203 citations

    3

    h-index

  3. IF
    I. Fisk

    European Organization for Nuclear Research, Switzerland

    2 publications · 984 citations

    2

    h-index

  4. ZZ
    Zhu Zhang

    Hong Kong Baptist University, Hong Kong SAR China

    2 publications · 45 citations

    2

    h-index

  5. DB
    Daniel Berenberg

    New York University, United States

    2 publications · 984 citations

    2

    h-index

1–5 of 238

Venues

  1. Bioinformatics

    11 publications · 1.2K citations

    10

    h-index

  2. 6

    h-index

  3. Nature Communications

    4 publications · 1K citations

    4

    h-index

  4. PLoS ONE

    4 publications · 96 citations

    4

    h-index

  5. Briefings in Bioinformatics

    3 publications · 177 citations

    3

    h-index

1–5