ArticlePLoS computational biology2022
A quantitative modelling approach for DNA repair on a population scale.
Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers.
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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.
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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
5 citing papers in PubMed.
- Understanding Cancer Health Disparities.Cancers · 2026Review
- AI-based methods for the assessment of DNA damage and repair mechanisms.Frontiers in systems biology · 2026Review
- The next-generation sequencing-chess problem.NAR genomics and bioinformatics · 2024Article
- DNA lesion bypass and the stochastic dynamics of transcription-coupled repair.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Correction: A quantitative modelling approach for DNA repair on a population scale.PLoS computational biology · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The great advances of sequencing technologies allow the in vivo measurement of nuclear processes-such as DNA repair after UV exposure-over entire cell populations. However, data sets usually contain only a few samples over several hours, missing possibly important information in between time points. We developed a data-driven approach to analyse CPD repair kinetics over time in Saccharomyces cerevisiae. In contrast to other studies that consider sequencing signals as an average behaviour, we understand them as the superposition of signals from independent cells. By motivating repair as a stochastic process, we derive a minimal model for which the parameters can be conveniently estimated. We correlate repair parameters to a variety of genomic features that are assumed to influence repair, including transcription rate and nucleosome density. The clearest link was found for the transcription unit length, which has been unreported for budding yeast to our knowledge. The framework hence allows a comprehensive analysis of nuclear processes on a population scale.
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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.