ArticleMetabolites2020
On the Use of Correlation and MI as a Measure of Metabolite-Metabolite Association for Network Differential Connectivity Analysis.
Article in Metabolites, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Discriminatory plasma biomarkers predict specific clinical phenotypes of necrotizing soft-tissue infections.The Journal of clinical investigation · 2021Trial
- Lipid and aqueous metabolomic responses of lettuce (Food chemistry: X · 2026Article
- Targeted serum metabolomic profiling and machine learning approach in Alzheimer's disease using the Alzheimer's disease diagnostics clinical study (ADDIA) cohort.Journal of Alzheimer's disease : JAD · 2025Article
- Mixed and membrane-separated culturing of synthetic cyanobacteria-yeast consortia reveals metabolic cross-talk mimicking natural cyanolichens.Scientific reports · 2024Article
- Differences in Metabolite Profiles of Dihydroberberine and Micellar Berberine in Caco-2 Cells and Humans-A Pilot Study.International journal of molecular sciences · 2024Article
- Edge and modular significance assessment in individual-specific networks.Scientific reports · 2023Article
- Age- and Sex-Dependent Changes of Free Circulating Blood Metabolite and Lipid Abundances, Correlations, and Ratios.The journals of gerontology. Series A, Biological sciences and medical sciences · 2022Article
- Article
- The human milk proteome and allergy of mother and child: Exploring associations with protein abundances and protein network connectivity.Frontiers in immunology · 2022Article
- Potential cardiotoxicity induced by Euodiae Fructus:Frontiers in pharmacology · 2022Article
- Analysis of Metabolite and Lipid Association Networks Reveals Molecular Mechanisms Associated with 3-Month Mortality and Poor Functional Outcomes in Patients with Acute Ischemic Stroke after Thrombolytic Treatment with Recombinant Tissue Plasminogen Activator.Journal of proteome research · 2021Article
- Article
- Special Issue: Development and Application of Statistical Methods for Analyzing Metabolomics Data.Metabolites · 2021Article
- Systems biology for crop improvement.The plant genome · 2021Review
- Article
- Evaluation of Single Sample Network Inference Methods for Metabolomics-Based Systems Medicine.Journal of proteome research · 2021Article
- Seeing the forest for the trees: Retrieving plant secondary biochemical pathways from metabolome networks.Computational and structural biotechnology journal · 2021Review
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2 authors.
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Abstract
Metabolite differential connectivity analysis has been successful in investigating potential molecular mechanisms underlying different conditions in biological systems. Correlation and Mutual Information (MI) are two of the most common measures to quantify association and for building metabolite-metabolite association networks and to calculate differential connectivity. In this study, we investigated the performance of correlation and MI to identify significantly differentially connected metabolites. These association measures were compared on (i) 23 publicly available metabolomic data sets and 7 data sets from other fields, (ii) simulated data with known correlation structures, and (iii) data generated using a dynamic metabolic model to simulate real-life observed metabolite concentration profiles. In all cases, we found more differentially connected metabolites when using correlation indices as a measure for association than MI. We also observed that different MI estimation algorithms resulted in difference in performance when applied to data generated using a dynamic model. We concluded that there is no significant benefit in using MI as a replacement for standard Pearson's or Spearman's correlation when the application is to quantify and detect differentially connected metabolites.
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