Multi-view Association Learning

Multi-View Association Learning is a computational framework that integrates complementary information from multiple heterogeneous data views to model and infer associations across biological omics layers while preserving the intrinsic structure and modality-specific characteristics of each view.

19

Publications

1.8K

Citations

93

Authors

43

Institutions

Publications per year

2017–2026

17

Authors

93

  1. WP
    Wei Peng

    Kunming University of Science and Technology, China

    2 publications · 66 citations

    2

    h-index

  2. HS
    Hong‐Bin Shen

    Shanghai Jiao Tong University, China

    2 publications · 44 citations

    2

    h-index

  3. WD
    Wei Dai

    Kunming University of Science and Technology, China

    2 publications · 66 citations

    2

    h-index

  4. DY
    Dong‐Jun Yu

    Nanjing University of Science and Technology, China

    2 publications · 44 citations

    2

    h-index

  5. HC
    Hui Cui

    La Trobe University, Australia

    1 publications · 19 citations

    1

    h-index

1–5 of 93

Venues

  1. Briefings in Bioinformatics

    8 publications · 467 citations

    8

    h-index

  2. BMC Bioinformatics

    1 publications · 44 citations

    1

    h-index

  3. Information Sciences

    1 publications · 18 citations

    1

    h-index

  4. 1

    h-index

  5. Computer Vision and Image Understanding

    CVIU · 1 publications · 46 citations

    1

    h-index

1–5