ArticleBioinformatics (Oxford, England)2025
Eclipse: a Python package for alignment of two or more nontargeted LC-MS metabolomics datasets.
Article in Bioinformatics (Oxford, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- mzLearn as a data-driven LC/MS signal detection algorithm that enables pre-trained generative models for untargeted metabolomics.Communications chemistry · 2025Article
- Dissecting Genetic and Environmental Determinants of Plasma Molecular Signatures and Their Link to Type 2 Diabetes Risk.medRxiv : the preprint server for health sciences · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
summaryNontargeted LC-MS (liquid chromatography-tandem mass spectrometry) metabolomics datasets contain a wealth of information but present many challenges during analysis and processing. Often, two or more independently processed datasets must be aligned to form a complete dataset, but existing software does not fully meet our needs. For this, we have created an open-source Python package called Eclipse. Eclipse uses a novel graph-based approach to handle complex matching scenarios that arise from n > 2 datasets. AVAILABILITY AND IMPLEMENTATION: Eclipse is open source (https://github.com/broadinstitute/bmxp) and can be installed via "pip install bmxp."
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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.