ArticleScientific data2024
Comprehensive mass spectrometric metabolomic profiling of a chemically diverse collection of plants of the Celastraceae family.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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Who cites it
7 citing papers in PubMed.
- Enhancing Molecular Change: Iron-Mediated Photochemistry Increases DOM Transformation in Tropical Peatland Canals.Environmental science & technology · 2026Article
- Laccase-Catalyzed Biotransformation of Dihydrostilbenes and Phenanthrenes: A Route to Novel Natural Product Derivatives.ACS omega · 2026Article
- Catechin-Folate nano-niosomes from Osbeckia parvifolia Arn. induce apoptotic cell death in Ovarian cancer.Scientific reports · 2026Article
- Article
- LC-MS-based metabolomic characterization ofRSC advances · 2025Article
- A universal language for finding mass spectrometry data patterns.Nature methods · 2025Article
- Dereplication of secondary metabolites from Sophora flavescens using an LC-MS/MS-based molecular networking strategy.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Natural products exhibit interesting structural features and significant biological activities. The discovery of new bioactive molecules is a complex process that requires high-quality metabolite profiling data to properly target the isolation of compounds of interest and enable their complete structural characterization. The same metabolite profiling data can also be used to better understand chemotaxonomic links between species. This Data Descriptor details a dataset resulting from the untargeted liquid chromatography-mass spectrometry metabolite profiling of 76 natural extracts of the Celastraceae family. The spectral annotation results and related chemical and taxonomic metadata are shared, along with proposed examples of data reuse. This data can be further studied by researchers exploring the chemical diversity of natural products. This can serve as a reference sample set for deep metabolome investigation of this chemically rich plant family.
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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 Socratic graph.