Graph-based Pathway Inference

Graph-Based Pathway Inference is a computational method that belongs to the class of pathway analysis techniques, distinguished by its use of graph-theoretical models to reconstruct or infer biological pathways from molecular interaction data based on network topology and connectivity patterns.

13

Publications

468

Citations

62

Authors

36

Institutions

Publications per year

2017–2026

2

Authors

62

  1. DK
    Dominic Ketley

    Cancer Research UK Scotland Institute, United Kingdom

    1 publications · 123 citations

    1

    h-index

  2. GS
    George S. Baillie

    University of Glasgow, United Kingdom

    1 publications · 123 citations

    1

    h-index

  3. ED
    Eduardo D. Sontag

    Rutgers, The State University of New Jersey, United States

    1 publications · 58 citations

    1

    h-index

  4. YL
    Yu‐Chuan Lin

    National Cheng Kung University, Taiwan

    1 publications · 11 citations

    1

    h-index

  5. TZ
    Thomas Zichner

    European Molecular Biology Laboratory, Germany

    1 publications · 19 citations

    1

    h-index

1–5 of 62

Venues

  1. Bioinformatics

    2 publications · 59 citations

    2

    h-index

  2. Science Signaling

    1 publications · 123 citations

    1

    h-index

  3. Computers & Chemical Engineering

    1 publications · 11 citations

    1

    h-index

  4. Nucleic Acids Research

    1 publications · 90 citations

    1

    h-index

  5. Algorithmica

    1 publications · 12 citations

    1

    h-index

1–5