Single-cell Network Inference

Single-Cell Network Inference is a computational methodology that distinguishes itself by reconstructing gene regulatory or cellular interaction networks from high-dimensional single-cell omics data, enabling the characterization of regulatory dynamics and functional relationships at individual cell resolution.

156

Publications

31.4K

Citations

818

Authors

312

Institutions

Publications per year

2017–2026

138

Authors

818

  1. QN
    Qing Nie

    University of California, Irvine, United States

    5 publications · 360 citations

    5

    h-index

  2. RC
    Robrecht Cannoodt

    VIB-UGent Center for Inflammation Research, Belgium

    4 publications · 269 citations

    4

    h-index

  3. YS
    Yvan Saeys

    Ghent University, Belgium

    4 publications · 269 citations

    4

    h-index

  4. OG
    Olivier Gandrillon

    Université Claude Bernard Lyon 1, France

    4 publications · 451 citations

    4

    h-index

  5. WS
    Wouter Saelens

    Ghent University, Belgium

    4 publications · 269 citations

    4

    h-index

1–5 of 818

Venues

  1. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 22 publications · 828 citations

    14

    h-index

  2. Bioinformatics

    15 publications · 1.6K citations

    13

    h-index

  3. Briefings in Bioinformatics

    10 publications · 424 citations

    10

    h-index

  4. Nucleic Acids Research

    11 publications · 1.1K citations

    10

    h-index

  5. PLoS Computational Biology

    4 publications · 96 citations

    4

    h-index

1–5