ArticleLife science alliance2023
Cost-effective DNA methylation profiling by FML-seq.
Article in Life science alliance, 2023. 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
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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
3 citing papers in PubMed.
- Circulating cell-free DNA methylation analysis of pancreatic cancer patients for early noninvasive diagnosis.Frontiers in oncology · 2025Article
- Droplet digital PCR analysis of CDH13 methylation status in Slovak women with invasive ductal breast cancer.Scientific reports · 2024Article
- Health equity engineering: Optimizing hope for a new generation of healthcare.Journal of clinical and translational science · 2024Article
Corrections and comments
- Update of
Authors and funding
3 authors.
Funding
Abstract
Current methods for profiling DNA methylation require costly reagents, sequencing, and labor time. We introduce fragmentation at methylated loci and sequencing (FML-seq), a sequencing library protocol that greatly reduces all these costs. Relative to other techniques tested on the same human cell lines, FML-seq produces similar measurements of absolute and differential cytosine methylation at a fraction of the price. FML-seq enables inexpensive, high-throughput experimental designs for large-scale epigenetics research projects.
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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.