9.4 Integration of proteomics data with other omics datasets
2 min read•july 25, 2024
combines data from various molecular technologies, offering a comprehensive view of biological systems. This approach reveals complex interactions and emergent properties that single-omics studies might miss, enhancing our understanding of disease mechanisms and advancing .
Integrating with other datasets, like and , uncovers and enzyme-metabolite relationships. Various tools and strategies help analyze this data, providing insights into , biomarkers, and network-based interpretations of biological processes.
Multi-Omics Data Integration
Concept of multi-omics integration
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Top images from around the web for Concept of multi-omics integration
Frontiers | Artificial Intelligence (AI)-Based Systems Biology Approaches in Multi-Omics Data ... View original
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Frontiers | Identification of Pan-Cancer Prognostic Biomarkers Through Integration of Multi ... View original
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Frontiers | Multi-omic Directed Networks Describe Features of Gene Regulation in Aged Brains and ... View original
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Frontiers | Artificial Intelligence (AI)-Based Systems Biology Approaches in Multi-Omics Data ... View original
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Multi-omics data integration combines data from multiple omics technologies (proteomics, , transcriptomics, metabolomics, ) providing comprehensive molecular profiles
Systems biology approach offers holistic view of biological systems revealing complex interactions between different molecular levels and emergent properties not visible in single-omics studies
Integration enhances biological insights, predictive power, novel biomarker identification, and disease mechanism understanding advancing personalized medicine (cancer treatment)
Integration of proteomics with other datasets
Proteomics and transcriptomics integration correlates protein and mRNA levels identifying post-transcriptional regulation mechanisms and events
Proteomics and metabolomics integration maps proteins to metabolic pathways revealing enzyme-metabolite relationships and protein-metabolite interactions (glycolysis)
Integration strategies involve:
and preprocessing
and
Statistical methods for (, , approaches)
Tools for multi-omics analysis
integrates experimental and predicted protein-protein interactions enabling functional enrichment analysis
software visualizes and analyzes networks with plugins for multi-omics data integration and topology analysis
performs multi-omics network analysis
integrates transcriptomics, proteomics, and metabolomics data