ArticleNature chemical biology2021
Chemically informed analyses of metabolomics mass spectrometry data with Qemistree.
Article in Nature chemical biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 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
57 citing papers in PubMed.
- eCOMET: an R package for evaluating metabolic diversity and enrichment from LC-MS/MS data to test ecological hypotheses from individuals to ecosystems.The New phytologist · 2026Article
- Trends in Computational Metabolomics: A Perspective on Five Years of Software Development, Challenges, and Opportunities (2021-2025).Analytical chemistry · 2026Review
- Tracking the Metabolites of Health and Disease Using Artificial Intelligence.Diseases (Basel, Switzerland) · 2026Review
- Navigating the conjugated metabolome.bioRxiv : the preprint server for biology · 2026Article
- Abyssal hydrothermal alteration drives the evolution from simple alkanes to prebiotic molecular complexity.Nature communications · 2026Article
- Stress-Induced Plant Specialized Metabolism: Signaling, Multi-Omics Integration, and Plant-Derived Antimicrobial Metabolites to Combat Antimicrobial Resistance.Plants (Basel, Switzerland) · 2026Review
- Recent Advances in Implementation of Machine Learning for Environmental Nontarget Identification.Environment & health (Washington, D.C.) · 2025Review
- LC-HRMS Coupling to Feature-Based Molecular Networking to Efficiently Annotate Monoterpene Indole Alkaloids ofPlants (Basel, Switzerland) · 2025Article
- Article
- Critical review on in silico methods for structural annotation of chemicals detected with LC/HRMS non-targeted screening.Analytical and bioanalytical chemistry · 2025Review
- Statistical analysis of feature-based molecular networking results from non-targeted metabolomics data.Nature protocols · 2025Article
- The iPhylo suite: an interactive platform for building and annotating biological and chemical taxonomic trees.Briefings in bioinformatics · 2024Article
- Leaf Endophytes Relationship with Host Metabolome Expression in Tropical Gymnosperms.Journal of chemical ecology · 2024Article
- Effects of individual traits vs. trait syndromes on assemblages of various herbivore guilds associated with central European Salix.Oecologia · 2024Article
- Machine learning of cellular metabolic rewiring.Biology methods & protocols · 2024Article
- Machine learning of cellular metabolic rewiring.bioRxiv : the preprint server for biology · 2023Article
- Illuminating the oral microbiome and its host interactions: recent advancements in omics and bioinformatics technologies in the context of oral microbiome research.FEMS microbiology reviews · 2023Review
- Microbiomes and metabolomes of dominant coral reef primary producers illustrate a potential role for immunolipids in marine symbioses.Communications biology · 2023Article
- Paired microbiome and metabolome analyses associate bile acid changes with colorectal cancer progression.Cell reports · 2023Article
- Recent advances in data- and knowledge-driven approaches to explore primary microbial metabolism.Current opinion in chemical biology · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
20 authors.
Funding
Abstract
Untargeted mass spectrometry is employed to detect small molecules in complex biospecimens, generating data that are difficult to interpret. We developed Qemistree, a data exploration strategy based on the hierarchical organization of molecular fingerprints predicted from fragmentation spectra. Qemistree allows mass spectrometry data to be represented in the context of sample metadata and chemical ontologies. By expressing molecular relationships as a tree, we can apply ecological tools that are designed to analyze and visualize the relatedness of DNA sequences to metabolomics data. Here we demonstrate the use of tree-guided data exploration tools to compare metabolomics samples across different experimental conditions such as chromatographic shifts. Additionally, we leverage a tree representation to visualize chemical diversity in a heterogeneous collection of samples. The Qemistree software pipeline is freely available to the microbiome and metabolomics communities in the form of a QIIME2 plugin, and a global natural products social molecular networking workflow.
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.