ArticleMolecular systems biology2009
Predicting metabolic biomarkers of human inborn errors of metabolism.
Article in Molecular systems biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 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
79 citing papers in PubMed, 172 citations in OpenAlex.
- Article
- GEMCAT-a new algorithm for gene expression-based prediction of metabolic alterations.NAR genomics and bioinformatics · 2025Article
- Genome scale metabolic network modelling for metabolic profile predictions.PLoS computational biology · 2024Article
- Modeling Red Blood Cell Metabolism in the Omics Era.Metabolites · 2023Review
- A Review of Disparities and Unmet Newborn Screening Needs over 33 Years in a Cohort of Mexican Patients with Inborn Errors of Intermediary Metabolism.International journal of neonatal screening · 2023Article
- A holistic view of muscle metabolic reprogramming through personalized metabolic modeling in newly diagnosed diabetic patients.PloS one · 2023Article
- Reduning Injection prevents carrageenan-induced inflammation in rats by serum and urine metabolomics analysis.Chinese herbal medicines · 2022Article
- Article
- Integrated genomic-metabolic classification of acute myeloid leukemia defines a subgroup with NPM1 and cohesin/DNA damage mutations.Leukemia · 2021Article
- A dynamic multi-tissue model to study human metabolism.NPJ systems biology and applications · 2021Article
- UPLC-Q-TOF/MS-Based Serum Metabolomics Reveals the Anti-Ischemic Stroke Mechanism of Nuciferine in MCAO Rats.ACS omega · 2020Article
- Fibroblast-specific genome-scale modelling predicts an imbalance in amino acid metabolism in Refsum disease.The FEBS journal · 2020Article
- Towards the routine use of in silico screenings for drug discovery using metabolic modelling.Biochemical Society transactions · 2020Review
- FastMM: an efficient toolbox for personalized constraint-based metabolic modeling.BMC bioinformatics · 2020Article
- Genome-Scale Model-Based Identification of Metabolite Indicators for Early Detection of Kidney Toxicity.Toxicological sciences : an official journal of the Society of Toxicology · 2020Article
- Current Status and Future Prospects of Genome-Scale Metabolic Modeling to Optimize the Use of Mesenchymal Stem Cells in Regenerative Medicine.Frontiers in bioengineering and biotechnology · 2020Review
- Review
- Mechanistic identification of biofluid metabolite changes as markers of acetaminophen-induced liver toxicity in rats.Toxicology and applied pharmacology · 2019Article
- Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0.Nature protocols · 2019Article
- Genome-Scale Metabolic Modeling from Yeast to Human Cell Models of Complex Diseases: Latest Advances and Challenges.Methods in molecular biology (Clifton, N.J.) · 2019Article
19 more citing papers are in PubMed but not listed here.
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 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Early diagnosis of inborn errors of metabolism is commonly performed through biofluid metabolomics, which detects specific metabolic biomarkers whose concentration is altered due to genomic mutations. The identification of new biomarkers is of major importance to biomedical research and is usually performed through data mining of metabolomic data. After the recent publication of the genome-scale network model of human metabolism, we present a novel computational approach for systematically predicting metabolic biomarkers in stochiometric metabolic models. Applying the method to predict biomarkers for disruptions of red-blood cell metabolism demonstrates a marked correlation with altered metabolic concentrations inferred through kinetic model simulations. Applying the method to the genome-scale human model reveals a set of 233 metabolites whose concentration is predicted to be either elevated or reduced as a result of 176 possible dysfunctional enzymes. The method's predictions are shown to significantly correlate with known disease biomarkers and to predict many novel potential biomarkers. Using this method to prioritize metabolite measurement experiments to identify new biomarkers can provide an order of a 10-fold increase in biomarker detection performance.
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.