Multi-omics integration in biomedical research - A metabolomics-centric review

Area of Science:

• Biotechnology
• Bioinformatics
• Systems Biology

Background:

• High-throughput technologies enable multi-omics profiling (genomics, transcriptomics, metabolomics).
• Vast biological data generated requires integration for understanding health and disease.
• Integrating multi-omics data is challenging due to dimensionality, heterogeneity, and lack of universal protocols.

Purpose of the Study:

• Provide an overview of multi-omics workflows.
• Focus on integration methods combining metabolomics with two or more omics layers.
• Discuss integration concepts for comprehensive biological system analysis.

Main Methods:

• Overview of typical multi-omics workflow.
• Discussion of data-driven, knowledge-based, simultaneous, and step-wise integration approaches.
• Highlighting applications in recent multi-omics studies.

Main Results:

• Detailed discussion of integration methods for multi-omics data.
• Examples of large-scale integration efforts.
• Exploration of combining metabolomics with other omics layers.

Conclusions:

• Multi-omics integration is crucial for deciphering complex biological systems.
• Various integration strategies exist, each with specific applications.
• This review offers a framework for advanced multi-omics data analysis.