ReviewAnnual review of analytical chemistry (Palo Alto, Calif.)2019
Challenges in Identifying the Dark Molecules of Life.
Review in Annual review of analytical chemistry (Palo Alto, Calif.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 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
32 citing papers in PubMed.
- From known chemical space to unannotated metabolites: a cluster-guided retention-time driven framework for biologically informed annotation.Metabolomics : Official journal of the Metabolomic Society · 2026Article
- The Language of Elution: Autoregressive Prediction of the Next Feature in Untargeted LC-HRMS Lipidomics.ArXiv · 2026Article
- Assessing the metabolomics "dark matter" by a detectable khipu model.Metabolomics : Official journal of the Metabolomic Society · 2026Article
- Review
- The dark matter in cancer immunology: beyond the visible- unveiling multiomics pathways to breakthrough therapies.Journal of translational medicine · 2025Review
- Pools of Independently Cycling Inositol Phosphates Revealed by Pulse Labeling withJournal of the American Chemical Society · 2025Article
- Lethal metabolism of Candida albicans respiratory mutants.PloS one · 2024Article
- MSdeCIpher: A Tool to Link Data from Complementary Ionization Techniques in High-Resolution GC-MS to Identify Molecular Ions.Metabolites · 2023Article
- Computational Expansion of High-Resolution-MSAnalytical chemistry · 2023Article
- Assessing How Chemical Exposures Affect Human Health.LC GC Europe · 2023Article
- Model-driven data curation pipeline for LC-MS-based untargeted metabolomics.Metabolomics : Official journal of the Metabolomic Society · 2023Article
- Unsupervised Analysis of Small Molecule Mixtures by Wavelet-Based Super-Resolved NMR.Molecules (Basel, Switzerland) · 2023Article
- Spatial metabolomics in head and neck tumors: a review.Frontiers in oncology · 2023Review
- Problems, principles and progress in computational annotation of NMR metabolomics data.Metabolomics : Official journal of the Metabolomic Society · 2022Review
- Metabolomics and modelling approaches for systems metabolic engineering.Metabolic engineering communications · 2022Review
- Methods for Quantifying the Metabolic Boundary Fluxes of Cell Cultures in Large Cohorts by High-Resolution Hydrophilic Liquid Chromatography Mass Spectrometry.Analytical chemistry · 2022Article
- Uncovering PFAS and Other Xenobiotics in the Dark Metabolome Using Ion Mobility Spectrometry, Mass Defect Analysis, and Machine Learning.Environmental science & technology · 2022Article
- The Potential Role of Metabolomics in Drug-Induced Liver Injury (DILI) Assessment.Metabolites · 2022Review
- Analysis of per- and polyfluoroalkyl substances in Houston Ship Channel and Galveston Bay following a large-scale industrial fire using ion-mobility-spectrometry-mass spectrometry.Journal of environmental sciences (China) · 2022Article
- Microbial containment device: A platform for comprehensive analysis of microbial metabolism without sample preparation.Frontiers in microbiology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Metabolomics is the study of the metabolome, the collection of small molecules in living organisms, cells, tissues, and biofluids. Technological advances in mass spectrometry, liquid- and gas-phase separations, nuclear magnetic resonance spectroscopy, and big data analytics have now made it possible to study metabolism at an omics or systems level. The significance of this burgeoning scientific field cannot be overstated: It impacts disciplines ranging from biomedicine to plant science. Despite these advances, the central bottleneck in metabolomics remains the identification of key metabolites that play a class-discriminant role. Because metabolites do not follow a molecular alphabet as proteins and nucleic acids do, their identification is much more time consuming, with a high failure rate. In this review, we critically discuss the state-of-the-art in metabolite identification with specific applications in metabolomics and how technologies such as mass spectrometry, ion mobility, chromatography, and nuclear magnetic resonance currently contribute to this challenging task.
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.