ArticleScientific reports2016
A deformation energy-based model for predicting nucleosome dyads and occupancy.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 17 citations in OpenAlex.
- Positional interpretation of cis-regulatory code and nucleosome organization with deep learning models.Nature communications · 2026Article
- Contributions of DNA mechanics and trans-regulation to nucleosome positioning in Schizosaccharomyces pombe and its role in co-transcriptional splicing.Epigenetics & chromatin · 2026Article
- HDGS-Net: nucleosome occupancy prediction based on a hybrid dilated gated separable convolutional neural network.BMC genomics · 2026Article
- DNA Sequence-Dependent Properties of Nucleosome Positioning in Regions of Distinct Chromatin States in Mouse Embryonic Stem Cells.International journal of molecular sciences · 2022Article
- A deformation energy model reveals sequence-dependent property of nucleosome positioning.Chromosoma · 2021Article
- Epigenetic Marks and Variation of Sequence-Based Information Along Genomic Regions Are Predictive of Recombination Hot/Cold Spots inFrontiers in genetics · 2021Article
- Deform-nu: A DNA Deformation Energy-Based Predictor for Nucleosome Positioning.Frontiers in cell and developmental biology · 2020Article
- The implication of DNA bending energy for nucleosome positioning and sliding.Scientific reports · 2018Article
- CAME: identification of chromatin accessibility from nucleosome occupancy and methylome sequencing.Bioinformatics (Oxford, England) · 2017Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Nucleosome plays an essential role in various cellular processes, such as DNA replication, recombination, and transcription. Hence, it is important to decode the mechanism of nucleosome positioning and identify nucleosome positions in the genome. In this paper, we present a model for predicting nucleosome positioning based on DNA deformation, in which both bending and shearing of the nucleosomal DNA are considered. The model successfully predicted the dyad positions of nucleosomes assembled in vitro and the in vitro map of nucleosomes in Saccharomyces cerevisiae. Applying the model to Caenorhabditis elegans and Drosophila melanogaster, we achieved satisfactory results. Our data also show that shearing energy of nucleosomal DNA outperforms bending energy in nucleosome occupancy prediction and the ability to predict nucleosome dyad positions is attributed to bending energy that is associated with rotational positioning of nucleosomes.
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