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Related Concept Videos

Nucleosome Remodeling02:54

Nucleosome Remodeling

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Nucleosomes are the basic units of chromatin compaction. Each nucleosome consists of the DNA bound tightly around a histone core, which makes the DNA inaccessible to DNA binding proteins such as DNA polymerase and RNA polymerase. Hence, the fundamental problem is to ensure access to DNA when appropriate, despite the compact and protective chromatin structure.
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Nucleosomes are the DNA-histone complex, where the DNA strand is wound around the histone core. The histone core is an octamer containing two copies of H2A, H2B, H3, and H4 histone proteins.
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Nucleosomes are the DNA-histone complex, where the DNA strand is wound around the histone core. The histone core is an octamer containing two copies of H2A, H2B, H3, and H4 histone proteins.
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DNA in a human cell is almost 2m long and it is packed inside a tiny nucleus that is only a few microns in diameter. The level of compaction of DNA inside the nucleus is astonishing. It is organized into several sequentially higher levels of compaction to fit into such a tiny space. The most compact form of DNA is a chromosome that can be seen under a microscope in a dividing cell.
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Chromatin Immunoprecipitation- ChIP02:36

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Chromatin immunoprecipitation, or ChIP, is an antibody-based technique used to identify sites on DNA that bind to transcription factors of interest or histone proteins. It also helps determine the type of histone modifications such as acetylation, phosphorylation, or methylation.
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Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
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Updated: Mar 6, 2026

Generation of Native Chromatin Immunoprecipitation Sequencing Libraries for Nucleosome Density Analysis
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Generation of Native Chromatin Immunoprecipitation Sequencing Libraries for Nucleosome Density Analysis

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Benchmarking and refining probability-based models for nucleosome-DNA interaction.

Marco Tompitak1, Gerard T Barkema2, Helmut Schiessel3

  • 1Lorentz Institute, Leiden University, Niels Bohrweg 2, Leiden, 2333CA, The Netherlands. tompitak@lorentz.leidenuniv.nl.

BMC Bioinformatics
|March 9, 2017
PubMed
Summary
This summary is machine-generated.

Markov chain models can approximate biophysical models for nucleosome positioning, enabling faster predictions and benchmarking. Model performance depends on order, data preprocessing, and sequence ensemble quality.

Keywords:
ModelingNucleosome positioningSequence analysis

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Area of Science:

  • Computational Biology
  • Genomics
  • Biophysics

Background:

  • Predicting nucleosome positioning requires sequence affinity models.
  • Markov chain models are a successful class of models for this purpose.

Purpose of the Study:

  • To explore the use of Markov chain models as fast approximations for biophysical models.
  • To benchmark these approximative in silico models.

Main Methods:

  • Utilizing Markov chain models informed by experimental nucleosomal sequence preferences.
  • Applying these models as a fast approximation scheme for computationally intensive biophysical models.

Main Results:

  • Markov chain models can serve as a fast approximation for biophysical models, significantly expanding their applicability.
  • This approach allows for the first-time benchmarking of these approximative models.
  • Benchmarking provides insights into the expected accuracy of these models on real biological data.

Conclusions:

  • Existing literature models are expected to perform well.
  • Model performance is contingent upon the Markov model's order.
  • Data preprocessing and the size/quality of the sequence ensemble are critical factors influencing model accuracy.