ArticleBioinformatics advances2023
MetChem: a new pipeline to explore structural similarity across metabolite modules.
Article in Bioinformatics advances, 2023. 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
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Who cites it
2 citing papers in PubMed.
- The tip of the iceberg: Profiling cooling agents using computational approaches to inform tobacco regulatory science.PloS one · 2026Article
- Metabolic Alterations in Colombian Women with Rheumatoid Arthritis and Systemic Lupus Erythematosus Reveal Potential Lipid Biomarkers Associated with Inflammation and Cardiovascular Risk.International journal of molecular sciences · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Summary: Computational analysis and interpretation of metabolomic profiling data remains a major challenge in translational research. Exploring metabolic biomarkers and dysregulated metabolic pathways associated with a patient phenotype could offer new opportunities for targeted therapeutic intervention. Metabolite clustering based on structural similarity has the potential to uncover common underpinnings of biological processes. To address this need, we have developed the MetChem package. MetChem is a quick and simple tool that allows to classify metabolites in structurally related modules, thus revealing their functional information. Availabilityand implementation: MetChem is freely available from the R archive CRAN (http://cran.r-project.org). The software is distributed under the GNU General Public License (version 3 or later).
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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.