ArticleNucleus (Austin, Tex.)2016
Simulating topological domains in human chromosomes with a fitting-free model.
Article in Nucleus (Austin, Tex.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- One chromatin, many structures: From ensemble contact maps to single-cell 3D organization.Biophysical journal · 2026Article
- One Chromatin, Many Structures: From Ensemble Contact Maps to Single-Cell 3D Organization.bioRxiv : the preprint server for biology · 2026Article
- Polymer Modeling Predicts Chromosome Reorganization in Senescence.Cell reports · 2019Article
- Shaping epigenetic memory via genomic bookmarking.Nucleic acids research · 2018Article
- Epigenetic Transitions and Knotted Solitons in Stretched Chromatin.Scientific reports · 2017Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We discuss a polymer model for the 3D organization of human chromosomes. A chromosome is represented by a string of beads, with each bead being "colored" according to 1D bioinformatic data (e.g., chromatin state, histone modification, GC content). Individual spheres (representing bi- and multi-valent transcription factors) can bind reversibly and selectively to beads with the appropriate color. During molecular dynamics simulations, the factors bind, and the string spontaneously folds into loops, rosettes, and topologically-associating domains (TADs). This organization occurs in the absence of any specified interactions between distant DNA segments, or between transcription factors. A comparison with Hi-C data shows that simulations predict the location of most boundaries between TADs correctly. The model is "fitting-free" in the sense that it does not use Hi-C data as an input; consequently, one of its strengths is that it can - in principle - be used to predict the 3D organization of any region of interest, or whole chromosome, in a given organism, or cell line, in the absence of existing Hi-C data. We discuss how this simple model might be refined to include more transcription factors and binding sites, and to correctly predict contacts between convergent CTCF binding sites.
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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.