ArticleNucleic acids research2015
Assessing the limits of restraint-based 3D modeling of genomes and genomic domains.
Article in Nucleic acids research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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Who cites it
39 citing papers in PubMed.
- Reconstructing 3D chromosome structures from single-cell Hi-C data with SO(3)-equivariant graph neural networks.NAR genomics and bioinformatics · 2025Article
- Polymer Physics Models Reveal Structural Folding Features of Single-Molecule Gene Chromatin Conformations.International journal of molecular sciences · 2024Article
- [An identification method of chromatin topological associated domains based on spatial density clustering].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2024Article
- Enhancer-driven 3D chromatin domain folding modulates transcription in human mammary tumor cells.Life science alliance · 2024Article
- Hi-BDiSCO: folding 3D mesoscale genome structures from Hi-C data using brownian dynamics.Nucleic acids research · 2024Article
- Techniques for and challenges in reconstructing 3D genome structures from 2D chromosome conformation capture data.Current opinion in cell biology · 2023Review
- HiC-GNN: A generalizable model for 3D chromosome reconstruction using graph convolutional neural networks.Computational and structural biotechnology journal · 2023Article
- TOAST: A novel method for identifying topologically associated domains based on graph auto-encoders and clustering.Computational and structural biotechnology journal · 2023Article
- KSHV Topologically Associating Domains in Latent and Reactivated Viral Chromatin.Journal of virology · 2022Article
- Integration of software tools for integrative modeling of biomolecular systems.Journal of structural biology · 2022Article
- CASPIAN: A method to identify chromatin topological associated domains based on spatial density cluster.Computational and structural biotechnology journal · 2022Article
- Article
- Inferring Single-Cell 3D Chromosomal Structures Based on the Lennard-Jones Potential.International journal of molecular sciences · 2021Article
- 3D reconstruction of genomic regions from sparse interaction data.NAR genomics and bioinformatics · 2021Article
- Polymer modelling unveils the roles of heterochromatin and nucleolar organizing regions in shaping 3D genome organization in Arabidopsis thaliana.Nucleic acids research · 2021Article
- Dynamics of genome architecture and chromatin function during human B cell differentiation and neoplastic transformation.Nature communications · 2021Article
- Computational approaches for inferring 3D conformations of chromatin from chromosome conformation capture data.Methods (San Diego, Calif.) · 2020Review
- Computational methods for predicting 3D genomic organization from high-resolution chromosome conformation capture data.Briefings in functional genomics · 2020Article
- Transcriptional activation during cell reprogramming correlates with the formation of 3D open chromatin hubs.Nature communications · 2020Article
- Assessing stationary distributions derived from chromatin contact maps.BMC bioinformatics · 2020Article
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6 authors.
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Abstract
Restraint-based modeling of genomes has been recently explored with the advent of Chromosome Conformation Capture (3C-based) experiments. We previously developed a reconstruction method to resolve the 3D architecture of both prokaryotic and eukaryotic genomes using 3C-based data. These models were congruent with fluorescent imaging validation. However, the limits of such methods have not systematically been assessed. Here we propose the first evaluation of a mean-field restraint-based reconstruction of genomes by considering diverse chromosome architectures and different levels of data noise and structural variability. The results show that: first, current scoring functions for 3D reconstruction correlate with the accuracy of the models; second, reconstructed models are robust to noise but sensitive to structural variability; third, the local structure organization of genomes, such as Topologically Associating Domains, results in more accurate models; fourth, to a certain extent, the models capture the intrinsic structural variability in the input matrices and fifth, the accuracy of the models can be a priori predicted by analyzing the properties of the interaction matrices. In summary, our work provides a systematic analysis of the limitations of a mean-field restrain-based method, which could be taken into consideration in further development of methods as well as their applications.
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