ReviewEndocrinology and metabolism (Seoul, Korea)2020
Systems Biology: A Multi-Omics Integration Approach to Metabolism and the Microbiome.
Review in Endocrinology and metabolism (Seoul, Korea), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 20 citations in OpenAlex.
- Obesity and Natural Products: Mechanisms, Therapeutic Potential, and Future Directions.Food science & nutrition · 2026Review
- Interplay of Microbiome, Oxidative Stress and Inflammation in Health and Disease.Antioxidants (Basel, Switzerland) · 2026Review
- Pathway-Specific Insights into Colorectal Cancer Through Comprehensive Multi-Omics Data Integration.Biology · 2025Article
- β-cell heterogeneity and molecular plasticity in type 2 diabetes: multi-omics perspectives and the role of gut microbiota.Frontiers in cell and developmental biology · 2025Review
- Review
- When the microbiome meets One Health principle: Leading to the Holy Grail of biology and contributing to overall well-being and social sustainability.iMetaOmics · 2024Review
- The Future Exploring of Gut Microbiome-Immunity Interactions: From In Vivo/Vitro Models to In Silico Innovations.Microorganisms · 2024Review
- Multiomics data integration, limitations, and prospects to reveal the metabolic activity of the coral holobiont.FEMS microbiology ecology · 2024Review
- Innovative Therapeutic Approaches in Non-Alcoholic Fatty Liver Disease: When Knowing Your Patient Is Key.International journal of molecular sciences · 2023Review
- Oxymatrine Alleviates High-Fat-High-Fructose-Induced Fatty Liver in Rats: Understanding the Molecular Mechanism Through an Untargeted Metabonomics Study.Diabetes, metabolic syndrome and obesity : targets and therapy · 2023Article
- Advances in Microbiome-Derived Solutions and Methodologies Are Founding a New Era in Skin Health and Care.Pathogens (Basel, Switzerland) · 2022Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 3 countries.
Funding
Abstract
The complex and dynamic nature of human physiology, as exemplified by metabolism, has often been overlooked due to the lack of quantitative and systems approaches. Recently, systems biology approaches have pushed the boundaries of our current understanding of complex biochemical, physiological, and environmental interactions, enabling proactive medicine in the near future. From this perspective, we review how state-of-the-art computational modelling of human metabolism, i.e., genome-scale metabolic modelling, could be used to identify the metabolic footprints of diseases, to guide the design of personalized treatments, and to estimate the microbiome contributions to host metabolism. These state-of-the-art models can serve as a scaffold for integrating multi-omics data, thereby enabling the identification of signatures of dysregulated metabolism by systems approaches. For example, increased plasma mannose levels due to decreased uptake in the liver have been identified as a potential biomarker of early insulin resistance by multi-omics approaches. In addition, we also review the emerging axis of human physiology and the human microbiome, discussing its contribution to host metabolism and quantitative approaches to study its variations in individuals.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.