ArticleChemical communications (Cambridge, England)2023
Sequencing for oxidative DNA damage at single-nucleotide resolution with click-code-seq v2.0.
Article in Chemical communications (Cambridge, England), 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
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
2 citing papers in PubMed.
- Click-code-seq reveals strand biases of DNA oxidation and depurination in human genome.Nature chemical biology · 2026Article
- Single-cell parallel analysis of DNA damage and transcriptome reveals selective genome vulnerability.Nature methods · 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
3 authors.
Funding
Abstract
Oxidative damage to DNA nucleotides has many cellular outcomes that could be aided by the development of sequencing methods. Herein, the previously reported click-code-seq method for sequencing a single damage type is redeveloped to enable the sequencing of many damage types by making simple changes to the protocol (
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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.