Feature Selection For Multi-omics

Feature Selection for Multi-Omics is a computational methodology within multi-omics data analysis that identifies and prioritizes biologically relevant features across distinct molecular layers by integrating and reducing high-dimensional heterogeneous datasets to enhance interpretability, model performance, and biological insight.

107

Publications

11.9K

Citations

509

Authors

296

Institutions

Publications per year

2017–2026

86

Authors

509

  1. GC
    George C. Tseng

    University of Pittsburgh, United States

    5 publications · 178 citations

    5

    h-index

  2. KL
    Kim‐Anh Lê Cao

    The University of Queensland, Australia

    4 publications · 6K citations

    4

    h-index

  3. QL
    Qi Long

    Emory University, United States

    4 publications · 92 citations

    4

    h-index

  4. YE
    Yasser EL‐Manzalawy

    Pennsylvania State University, United States

    3 publications · 97 citations

    3

    h-index

  5. BG
    Benoît Gautier

    Inserm, France

    3 publications · 5.4K citations

    3

    h-index

1–5 of 509

Venues

  1. Bioinformatics

    13 publications · 1.6K citations

    13

    h-index

  2. Briefings in Bioinformatics

    7 publications · 411 citations

    7

    h-index

  3. BMC Bioinformatics

    6 publications · 240 citations

    6

    h-index

  4. Frontiers in Genetics

    6 publications · 376 citations

    6

    h-index

  5. Biostatistics

    4 publications · 405 citations

    4

    h-index

1–5