ArticleComputational and structural biotechnology journal2013
Error Analysis and Propagation in Metabolomics Data Analysis.
Article in Computational and structural biotechnology journal, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Information-Content-Informed Kendall-Tau Correlation Methodology: Interpreting Missing Values in Metabolomics as Potentially Useful Information.Metabolites · 2026Article
- Age- and sex-associated effects of C18 ceramide sphingolipids on osteoclastogenesis in experimental models of Gulf War Illness.Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · 2025Article
- Disrupted fetal carbohydrate metabolism in children with autism spectrum disorder.Journal of neurodevelopmental disorders · 2025Article
- Statistical analysis of feature-based molecular networking results from non-targeted metabolomics data.Nature protocols · 2025Article
- Multiplatform untargeted metabolomics.Magnetic resonance in chemistry : MRC · 2023Review
- Scan-Centric, Frequency-Based Method for Characterizing Peaks from Direct Injection Fourier Transform Mass Spectrometry Experiments.Metabolites · 2022Article
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- Statistical analysis in metabolic phenotyping.Nature protocols · 2021Article
- Versatile Functional Energy Metabolism Platform Working From Research to Patient: An Integrated View of Cell Bioenergetics.Frontiers in toxicology · 2021Review
- Deriving Lipid Classification Based on Molecular Formulas.Metabolites · 2020Article
- Article
- Improved workflow for mass spectrometry-based metabolomics analysis of the heart.The Journal of biological chemistry · 2020Article
- Corruption of the Pearson correlation coefficient by measurement error and its estimation, bias, and correction under different error models.Scientific reports · 2020Article
- Moiety modeling framework for deriving moiety abundances from mass spectrometry measured isotopologues.BMC bioinformatics · 2019Article
- Systems biology: perspectives on multiscale modeling in research on endocrine-related cancers.Endocrine-related cancer · 2019Review
- A Tool to Encourage Minimum Reporting Guideline Uptake for Data Analysis in Metabolomics.Metabolites · 2019Article
- Advances in gene ontology utilization improve statistical power of annotation enrichment.PloS one · 2019Article
- Article
- New methods to identify high peak density artifacts in Fourier transform mass spectra and to mitigate their effects on high-throughput metabolomic data analysis.Metabolomics : Official journal of the Metabolomic Society · 2018Article
- Integration of metabolomics and transcriptomics in nanotoxicity studies.BMB reports · 2018Article
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Abstract
Error analysis plays a fundamental role in describing the uncertainty in experimental results. It has several fundamental uses in metabolomics including experimental design, quality control of experiments, the selection of appropriate statistical methods, and the determination of uncertainty in results. Furthermore, the importance of error analysis has grown with the increasing number, complexity, and heterogeneity of measurements characteristic of 'omics research. The increase in data complexity is particularly problematic for metabolomics, which has more heterogeneity than other omics technologies due to the much wider range of molecular entities detected and measured. This review introduces the fundamental concepts of error analysis as they apply to a wide range of metabolomics experimental designs and it discusses current methodologies for determining the propagation of uncertainty in appropriate metabolomics data analysis. These methodologies include analytical derivation and approximation techniques, Monte Carlo error analysis, and error analysis in metabolic inverse problems. Current limitations of each methodology with respect to metabolomics data analysis are also discussed.
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