ArticleAnalytical chemistry2021
Expanding Urinary Metabolite Annotation through Integrated Mass Spectral Similarity Networking.
Article in Analytical chemistry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Insights into the activity, production, and signaling circuits of homoserine lactones in mammalian cells.iScience · 2026Article
- Network Pharmacology Combined With Metabonomics and Transcriptomics Reveals the Mechanism ofFood science & nutrition · 2026Article
- Cross ionization mode chemical similarity prediction between tandem mass spectra in metabolomics.Nature communications · 2026Article
- Identification and Distribution of the Dietary Antioxidant Ergothioneine in Humans and Animal Models Combining NMR, RANSY, and MS Methods.Analytical chemistry · 2025Article
- Longitudinal Fragment Profiles Based on Multi-Collision Energy Tandem Mass Spectra Improve the Accuracy of Metabolite Identification in Untargeted Metabolomics.Analytical chemistry · 2025Article
- The Dietary Biomarkers Development Consortium: An Initiative for Discovery and Validation of Dietary Biomarkers for Precision Nutrition.Current developments in nutrition · 2025Article
- Characterization of the Composition of Bioactive Fractions fromFoods (Basel, Switzerland) · 2024Article
- Identification of Predictive Biomarkers of Lameness in Transition Dairy Cows.Animals : an open access journal from MDPI · 2024Article
- Electron-activated dissociation (EAD) for the complementary annotation of metabolites and lipids through data-dependent acquisition analysis and feature-based molecular networking, applied to the sentinel amphipod Gammarus fossarum.Analytical and bioanalytical chemistry · 2024Article
- Comprehensive Evaluation System for Post-Metabolic Activity of Potential Thyroid-Disrupting Chemicals.Journal of microbiology and biotechnology · 2023Article
- Article
- Fast screening and identification of illegal adulteration in dietary supplements and herbal medicines using molecular networking with deep-learning-based similarity algorithms.Analytical and bioanalytical chemistry · 2023Article
- Feature-Based Molecular Networking Facilitates the Comprehensive Identification of Differential Metabolites in Diabetic Cognitive Dysfunction Rats.Metabolites · 2023Article
- Enhancing Capacity for Food and Nutrient Intake Assessment in Population Sciences Research.Annual review of public health · 2023Review
- Spatial metabolomics reveals skeletal myofiber subtypes.Science advances · 2023Article
- Metabolite annotation from knowns to unknowns through knowledge-guided multi-layer metabolic networking.Nature communications · 2022Article
- Combining Feature-Based Molecular Networking and Contextual Mass Spectral Libraries to Decipher Nutrimetabolomics Profiles.Metabolites · 2022Article
- Evaluation of Ion Mobility Spectrometry for Improving Constitutional Assignment in Natural Product Mixtures.Journal of natural products · 2022Article
- Combination of GC-MS Molecular Networking and Larvicidal Effect againstMolecules (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
The urine metabolome constitutes a rich source of functional information reflecting physiological states that are influenced by distinct conditions and biological stresses, such as responses to drug treatments or disease manifestations. Although global liquid chromatography-mass spectrometry (MS) profiling provides the most comprehensive measurement of metabolites in complex biological samples, annotation remains a challenge, and computational approaches are necessary to translate the molecular composition into biological knowledge. Here, we investigated the use of tandem MS-based enhanced molecular networks (MolNetEnhancer) to improve the metabolite annotation of urine extracts. The samples (
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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.