Multi-omics Predictive Modeling
Multi-Omics Predictive Modeling is a computational framework that integrates diverse omics data types to construct predictive models for phenotypic or clinical outcomes, distinguished from other modeling approaches by its explicit incorporation of multi-layered biological data to enhance prediction accuracy and biological interpretability.
148
Publications
10.2K
Citations
1K
Authors
507
Institutions
Publications per year
2017–2026
135
Parents
148
Deep Learning–Based Multi-Omics Integration Robustly Predicts Survival in Liver Cancer
Kumardeep Chaudhary, Olivier Poirion, Liangqun Lu et al. · Clinical Cancer Research · 2017 · 1.1K citations · Full text
Medicine, Bioinformatics, Oncology +17
Multi-omic machine learning predictor of breast cancer therapy response
Stephen‐John Sammut, Mireia Crispin‐Ortuzar, Suet‐Feung Chin et al. · Nature · 2021 · 642 citations · Full text
Medicine, Cancer Biology, Oncology +17
1–5 of 148
1K
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2
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Barking, Havering And Redbridge University Hospitals NHS Trust, United Kingdom
2 publications · 52 citations
2
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2
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1–5 of 1K
507

Centre National de la Recherche Scientifique
Paris, France
6 h-index
18 publications
728 citations
Inserm
Paris, France
5 h-index
13 publications
922 citations
Harvard University
Cambridge, United States
5 h-index
11 publications
1.2K citations

Broad Institute
Cambridge, United States
4 h-index
6 publications
396 citations

University of Oslo
Oslo, Norway
4 h-index
7 publications
322 citations
University of Cambridge
Cambridge, United Kingdom
4 h-index
23 publications
9.3K citations
University of Michigan
Ann Arbor, United States
4 h-index
6 publications
741 citations

Imperial College London
London, United Kingdom
4 h-index
16 publications
837 citations
1–8 of 507
8 publications · 413 citations
8
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7 publications · 1.7K citations
7
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6 publications · 178 citations
6
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5 publications · 341 citations
5
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4 publications · 428 citations
4
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1–5