reviewBriefings in BioinformaticsJul 1, 2025GOLD OA

A technical review of multi-omics data integration methods: from classical statistical to deep generative approaches

ARAna R. BaiãoZCZhaoxiang CaiRCRebecca C. PoulosPJPhillip J. RobinsonRRRoger R. Reddel

Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento · Children's Medical Research Institute

PubMed
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Abstract

The rapid advancement of high-throughput sequencing and other assay technologies has resulted in the generation of large and complex multi-omics datasets, offering unprecedented opportunities for advancing precision medicine. However, multi-omics data integration remains challenging due to the high-dimensionality, heterogeneity, and frequency of missing values across data types. Computational methods leveraging statistical and machine learning approaches have been developed to address these issues and uncover complex biological patterns, improving our understanding of disease mechanisms. Here, we comprehensively review state-of-the-art multi-omics integration methods with a focus on deep generative models,…

Citation impact

96
total citations
FWCI
59.82
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100%
References
207
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Authors

8

Topics & keywords

Topics
Keywords
  • Computer science
  • Data integration
  • Generative grammar
  • Artificial intelligence
  • Deep learning
  • Machine learning
  • Precision medicine
  • Data science
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