Supervised Multi-omics Classification

Supervised Multi-Omics Classification is a multi-omics data integration framework that employs labeled training data to jointly analyze heterogeneous omics layers—such as genomics, transcriptomics, and metabolomics—using supervised machine learning algorithms to predict categorical biological outcomes.

8

Publications

315

Citations

53

Authors

23

Institutions

Publications per year

2017–2026

7

Authors

53

  1. VC
    Vincenzo Corbo

    University of Verona, Italy

    1 publications · 12 citations

    1

    h-index

  2. JZ
    Jingqing Zhang

    Massachusetts Institute of Technology, United States

    1 publications · 82 citations

    1

    h-index

  3. SK
    Suneel Kamath

    Cleveland Clinic, United States

    1 publications · 38 citations

    1

    h-index

  4. NA
    N. A. Wani

    Central Veterinary Research Laboratory, United Arab Emirates

    1 publications · 12 citations

    1

    h-index

  5. GS
    Gaya Spolverato

    Johns Hopkins University, United States

    1 publications · 12 citations

    1

    h-index

1–5 of 53

Venues

  1. BMC Bioinformatics

    2 publications · 54 citations

    2

    h-index

  2. Expert Systems with Applications

    1 publications · 43 citations

    1

    h-index

  3. 1

    h-index

  4. European Journal of Cancer

    1 publications · 12 citations

    1

    h-index

  5. PeerJ Computer Science

    1 publications · 12 citations

    1

    h-index

1–5