Multi-modal Single-cell Visualization

Multi-Modal Single-Cell Visualization is a computational visualization framework that integrates and graphically represents multiple types of molecular measurements—such as transcriptomic, epigenomic, and proteomic data—at single-cell resolution to enable joint analysis of diverse biological modalities within individual cells.

4

Publications

189

Citations

28

Authors

15

Institutions

Publications per year

2017–2026

4

Authors

28

  1. JF
    Jean‐Jacques Fournié

    Inserm, France

    1 publications · 20 citations

    1

    h-index

  2. YY
    Yueyuxiao Yang

    BGI Group (China), China

    1 publications · 63 citations

    1

    h-index

  3. AN
    Ashwin Narayan

    Broad Institute, United States

    1 publications · 44 citations

    1

    h-index

  4. BH
    Brian Hie

    Stanford University, United States

    1 publications · 44 citations

    1

    h-index

  5. HY
    Huanming Yang

    BGI Group (China), China

    1 publications · 63 citations

    1

    h-index

1–5 of 28

Venues

  1. Nature Methods

    1 publications · 62 citations

    1

    h-index

  2. Genome biology

    1 publications · 44 citations

    1

    h-index

  3. NAR Genomics and Bioinformatics

    1 publications · 20 citations

    1

    h-index

  4. Nature Machine Intelligence

    1 publications · 63 citations

    1

    h-index

1–4