ArticleBMC bioinformatics2017
Benchmarking and refining probability-based models for nucleosome-DNA interaction.
Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- In vitro reconstitution of chromatin replication recapitulates symmetric histone recycling.Nature communications · 2026Article
- Multiplexing mechanical and translational cues on genes.Biophysical journal · 2022Article
- The lane-switch mechanism for nucleosome repositioning by DNA translocase.Nucleic acids research · 2021Article
- Review
- Article
- Systematics for types and effects of DNA variations.BMC genomics · 2018Review
- The Latest Twists in Chromatin Remodeling.Biophysical journal · 2018Review
- The role of DNA sequence in nucleosome breathing.The European physical journal. E, Soft matter · 2017Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn investigations of nucleosome positioning preferences, a model that assigns an affinity to a given sequence is necessary to make predictions. One important class of models, which treats a nucleosome sequence as a Markov chain, has been applied with success when informed with experimentally measured nucleosomal sequence preferences.
resultsWe find that we can also use such models as a fast approximative scheme for computationally expensive biophysical models, vastly increasing their reach. Employing these models in this way also allows us to benchmark them for the first time. Doing so for the approximative in silico models indirectly tells us about the accuracy we can expect of them when applied to real data.
conclusionWe find that models presented in the literature should perform well, but this performance depends on factors such as the order of the Markov model, the preprocessing of the probability distributions on which the model is based, and the size and quality of the sequence ensemble from which those distributions are calculated.
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Registered trials
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