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Abstract <p>This review is devoted to diagonal integration of multi-omics data, an approach enabling to combine data from different molecular modalities obtained in independent studies without pairwise measurements. Twenty-two diagonal integration methods classified by mathematical basis are analyzed. A comparative analysis of international and Russian platforms is presented. A concept of a biocentric approach based on coupled Laplacians and kernel methods in reproducing Hilbert space is substantiated.</p>

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Diagonal Integration of Multi-Omics Biological Data: Methods, Tools, and Prospects

  • 期刊论文

  • 发表日期：

    2026年7月20日

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  • M. S. Arbatsky,
  • D. E. Balandin,
  • A. V. Churov

摘要

Abstract

This review is devoted to diagonal integration of multi-omics data, an approach enabling to combine data from different molecular modalities obtained in independent studies without pairwise measurements. Twenty-two diagonal integration methods classified by mathematical basis are analyzed. A comparative analysis of international and Russian platforms is presented. A concept of a biocentric approach based on coupled Laplacians and kernel methods in reproducing Hilbert space is substantiated.