ArticleNucleic acids research2025
MMEASE: enhanced analytical workflow for single-cell metabolomics.
Article in Nucleic acids research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Living single-cell metabolomicsChemical science · 2026Review
- Advanced technologies of single-cell metabolomics unveiling cellular metabolic heterogeneity for biological and biomedical research.Journal of food and drug analysis · 2026Review
- Metabolomics-Driven Precision Prevention and Treatment of Heart Failure with Traditional Chinese Medicine: From Mechanistic Insights to Metabolic Network Regulation.Drug design, development and therapy · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Metabolomics is essential for providing an overview of what chemical processes are taking place. A clear shift from bulk metabolomics to single-cell metabolomics (SCM) is observed in current research, and an integral workflow enabling the analysis of SCM data is therefore in great demand. However, no such workflow has been available to date. Herein, MMEASE, previously designed for analyzing bulk metabolomic data, was therefore updated to its 2.0 version by developing the first comprehensive and in-depth workflow analyzing SCM data. First, it provided all sequential steps of modern SCM research (from SCM data processing, to cellular heterogeneity analysis, then to high-resolution metabolite annotation, and finally to cell-based biological interpretation). Second, compared with the existing tools, MMEASE 2.0 was superior by incorporating the widest variety of methods at every step of the SCM analyses. The originality and functionality of our MMEASE were extensively validated and explicitly described by case studies on benchmark data. All in all, MMEASE 2.0 was unique in accomplishing comprehensive and in-depth analyses of SCM data, which could be considered as an indispensable complement to the existing tools. Now, the latest version of MMEASE is freely accessible by all users at: https://idrblab.org/mmease/.
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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.