Single-cell Visualization

Single-Cell Visualization is a data visualization methodology in single-cell bioinformatics that produces interactive, typically low-dimensional graphical representations of high-dimensional measurements from individual cells to enable the exploration, interpretation, and communication of cellular heterogeneity and structure.

506

Publications

59K

Citations

3K

Authors

829

Institutions

Publications per year

2017–2026

303

Authors

3K

  1. GP
    Garry P. Nolan

    Stanford University, United States

    10 publications · 4.3K citations

    10

    h-index

  2. SF
    Steven F. Lee

    University of Cambridge, United Kingdom

    5 publications · 1.4K citations

    5

    h-index

  3. BP
    Boudewijn P. F. Lelieveldt

    Leiden University Medical Center, Netherlands

    4 publications · 916 citations

    4

    h-index

  4. DJ
    Dechen Jiang

    Nanjing University, China

    4 publications · 199 citations

    4

    h-index

  5. SB
    Sarah Black

    Stanford University, United States

    4 publications · 2.5K citations

    4

    h-index

1–5 of 3K

Venues

  1. Nature Methods

    23 publications · 6.4K citations

    23

    h-index

  2. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 39 publications · 1.5K citations

    20

    h-index

  3. Bioinformatics

    22 publications · 6.7K citations

    19

    h-index

  4. Scientific Reports

    14 publications · 754 citations

    14

    h-index

  5. Nature Communications

    14 publications · 2.6K citations

    14

    h-index

1–5