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
Parents
8
1–5 of 8
53
1
h-index
1
h-index
1
h-index
1
h-index
1
h-index
1–5 of 53
23
Cleveland Clinic Lerner College of Medicine
Cleveland, United States
1 h-index
4 publications
152 citations
University of Verona
Verona, Italy
1 h-index
8 publications
96 citations

Imperial College London
London, United Kingdom
1 h-index
6 publications
492 citations

Jamia Millia Islamia
New Delhi, India
1 h-index
1 publications
12 citations

University of Padua
Padua, Italy
1 h-index
1 publications
12 citations
Emory University
Atlanta, United States
1 h-index
1 publications
12 citations
The University of Texas Health Science Center at Houston
Houston, United States
1 h-index
2 publications
84 citations
Case Comprehensive Cancer Center
Cleveland, United States
1 h-index
7 publications
266 citations
1–8 of 23
2 publications · 54 citations
2
h-index
1 publications · 43 citations
1
h-index
1 publications · 74 citations
1
h-index
1 publications · 12 citations
1
h-index
1 publications · 12 citations
1
h-index
1–5