Unsupervised Cell Type Annotation

Unsupervised Cell Type Annotation is a computational methodology in single-cell genomics that assigns cell type labels to unlabeled biological cells based on intrinsic patterns and structures discovered directly from high-dimensional transcriptomic data without relying on prior knowledge or reference datasets.

16

Publications

1.9K

Citations

103

Authors

51

Institutions

Publications per year

2017–2026

14

Authors

103

  1. OL
    Oscar L. Rodriguez

    University of Louisville, United States

    2 publications · 73 citations

    2

    h-index

  2. MM
    Michael M. Hoffman

    University of Toronto, Canada

    2 publications · 73 citations

    2

    h-index

  3. FW
    Fang Wang

    Tencent (China), China

    2 publications · 612 citations

    2

    h-index

  4. WS
    William Stafford Noble

    University of Washington, United States

    2 publications · 73 citations

    2

    h-index

  5. JH
    Junzhou Huang

    The University of Texas at Arlington, United States

    2 publications · 612 citations

    2

    h-index

1–5 of 103

Venues

  1. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 6 publications · 108 citations

    4

    h-index

  2. Nature Machine Intelligence

    2 publications · 649 citations

    2

    h-index

  3. Bioinformatics

    2 publications · 302 citations

    2

    h-index

  4. Nature Communications

    1 publications · 62 citations

    1

    h-index

  5. Diabetes

    1 publications · 480 citations

    1

    h-index

1–5