Latent Space Interpretation

Latent Space Interpretation is a computational framework in multi-omics analysis that identifies and characterizes biologically meaningful representations by decoding abstract, reduced-dimensional embeddings derived from heterogeneous omics data.

546

Publications

34.3K

Citations

2K

Authors

617

Institutions

Publications per year

2017–2026

455

Authors

2K

  1. BZ
    Bolei Zhou

    Chinese University of Hong Kong, Hong Kong SAR China

    6 publications · 1.7K citations

    6

    h-index

  2. YS
    Yujun Shen

    Chinese University of Hong Kong, Hong Kong SAR China

    5 publications · 1.7K citations

    5

    h-index

  3. AE
    Adrian E. Raftery

    University of Washington, United States

    4 publications · 1K citations

    4

    h-index

  4. DC
    Daniel Cohen‐Or

    Tel Aviv University, Israel

    4 publications · 1.1K citations

    4

    h-index

  5. MD
    Michael D. Ward

    Duke University, United States

    4 publications · 335 citations

    4

    h-index

1–5 of 2K

Venues

  1. arXiv (Cornell University)

    Repository · 68 publications · 3.5K citations

    24

    h-index

  2. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 11 publications · 488 citations

    13

    h-index

  3. ACM Transactions on Graphics

    TOG · 14 publications · 1.7K citations

    13

    h-index

  4. Bioinformatics

    12 publications · 764 citations

    12

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 9 publications · 1K citations

    11

    h-index

1–5