Unsupervised Multi-omics Clustering

Unsupervised Multi-Omics Clustering is a computational method that integrates diverse omics data types to identify inherent biological subgroups without prior knowledge of sample labels, thereby enabling hypothesis-free discovery of molecularly distinct patient or sample strata in a data-driven manner.

9

Publications

720

Citations

41

Authors

23

Institutions

Publications per year

2017–2026

7

Authors

41

  1. QZ
    Quan Zou

    University of Electronic Science and Technology of China, China

    1 publications · 27 citations

    1

    h-index

  2. MP
    Morgane Pierre‐Jean

    Centre National de Recherche en Génomique Humaine, France

    1 publications · 113 citations

    1

    h-index

  3. CX
    Chenyang Xie

    Sichuan University, China

    1 publications · 43 citations

    1

    h-index

  4. DW
    Dongfang Wang

    Tsinghua University, China

    1 publications · 237 citations

    1

    h-index

  5. AG
    Alexander Grishin

    Icahn School of Medicine at Mount Sinai, United States

    1 publications · 30 citations

    1

    h-index

1–5 of 41

Venues

  1. Briefings in Bioinformatics

    4 publications · 308 citations

    4

    h-index

  2. BMC Genomics

    1 publications · 237 citations

    1

    h-index

  3. Cell Reports

    1 publications · 30 citations

    1

    h-index

  4. iScience

    1 publications · 43 citations

    1

    h-index

  5. BMC Bioinformatics

    1 publications · 63 citations

    1

    h-index

1–5