Interpretability Of Clusters

Interpretability of Clusters is the extent to which the biological or functional meaning underlying cell subpopulations identified by clustering algorithms in single-cell data can be clearly understood and biologically validated by researchers.

50

Publications

4.1K

Citations

179

Authors

94

Institutions

Publications per year

2017–2026

25

Authors

179

  1. FV
    Fedor V. Fomin

    University of Bergen, Norway

    2 publications · 39 citations

    2

    h-index

  2. PO
    Patrick O. Perry

    New York University, United States

    2 publications · 89 citations

    2

    h-index

  3. DB
    Dimitris Bertsimas

    Massachusetts Institute of Technology, United States

    2 publications · 138 citations

    2

    h-index

  4. PA
    Petr A. Golovach

    University of Bergen, Norway

    2 publications · 39 citations

    2

    h-index

  5. SB
    Sayan Bandyapadhyay

    University of Bergen, Norway

    2 publications · 39 citations

    2

    h-index

1–5 of 179

Venues

  1. arXiv (Cornell University)

    Repository · 3 publications · 53 citations

    3

    h-index

  2. Information Sciences

    2 publications · 83 citations

    2

    h-index

  3. Pattern Analysis and Applications

    2 publications · 82 citations

    2

    h-index

  4. Soft Computing

    2 publications · 29 citations

    2

    h-index

  5. Pattern Recognition

    2 publications · 41 citations

    2

    h-index

1–5