ArticleACS measurement science au2026
FERMO: A Dashboard for Biochemometric Prioritization of Molecular Features from Mass Spectral Data.
Article in ACS measurement science au, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Computational metabolomics at scale: from open data to insight.Current opinion in biotechnology · 2026Review
- Integrated Omics-Based Discovery of Bioactive Halogenated Metabolites from the Deep-SeaMarine drugs · 2025Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Many natural products can selectively modulate biological processes, making them prime candidates for drug discovery. However, the complexity of biological samples makes clear attribution of activity to molecules challenging, thereby hampering hypothesis-driven prioritization, with liquid chromatography-tandem mass spectrometry routinely detecting hundreds of molecules per sample. Existing biochemometric tools typically focus on facilitating data-driven exploration to support manual interpretation, rather than more objective, data-driven prioritization and hypothesis generation. Here, we introduce FERMO, a free online dashboard interface for biochemometrics-based prioritization of molecular features and samples. FERMO accepts qualitative and quantitative bioactivity assay data and further integrates group metadata and results from genome mining. FERMO performs automated data processing, organization, and annotation, supporting prioritization with the calculation of custom scores. FERMO supports both exploratory and targeted analysis through efficient interactive visualization, reproducible prioritization, and data filtering. We demonstrate FERMO's utility in benchmarking studies prioritizing bioactive natural products from complex biological matrices. FERMO is freely available at https://fermo.bioinformatics.nl/.
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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.