ReviewFrontiers in genetics2020
Predicting Genome Architecture: Challenges and Solutions.
Review in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
26 citing papers in PubMed, 44 citations in OpenAlex.
- The 3D genomics of lampbrush chromosomes highlights the role of active transcription in chromatin organization.Nucleic acids research · 2026Article
- Reconstructing the 3D genome organization of Neanderthals reveals that chromatin folding shaped phenotypic and sequence divergence.bioRxiv : the preprint server for biology · 2025Article
- Direction and modality of transcription changes caused by TAD boundary disruption in Slc29a3/Unc5b locus depends on tissue-specific epigenetic context.Epigenetics & chromatin · 2025Article
- The challenge of chromatin model comparison and validation: A project from the first international 4D Nucleome Hackathon.PLoS computational biology · 2025Article
- Charm is a flexible pipeline to simulate chromosomal rearrangements on Hi-C-like data.NAR genomics and bioinformatics · 2025Article
- Combining chromosome conformation capture and exome sequencing for simultaneous detection of structural and single-nucleotide variants.Genome medicine · 2025Article
- GENA-LM: a family of open-source foundational DNA language models for long sequences.Nucleic acids research · 2025Article
- Machine and Deep Learning Methods for Predicting 3D Genome Organization.Methods in molecular biology (Clifton, N.J.) · 2025Review
- A review of deep learning models for the prediction of chromatin interactions with DNA and epigenomic profiles.Briefings in bioinformatics · 2024Review
- Structural variants in the Epb41l4a locus: TAD disruption and Nrep gene misregulation as hypothetical drivers of neurodevelopmental outcomes.Scientific reports · 2024Article
- Article
- Hi-BDiSCO: folding 3D mesoscale genome structures from Hi-C data using brownian dynamics.Nucleic acids research · 2024Article
- The haplotype-resolved telomere-to-telomere carnation (Horticulture research · 2024Article
- cudaMMC: GPU-enhanced multiscale Monte Carlo chromatin 3D modelling.Bioinformatics (Oxford, England) · 2023Article
- De novo assembly and annotation of the singing mouse genome.BMC genomics · 2023Article
- Techniques for and challenges in reconstructing 3D genome structures from 2D chromosome conformation capture data.Current opinion in cell biology · 2023Review
- Predicting chromosomal compartments directly from the nucleotide sequence with DNA-DDA.Briefings in bioinformatics · 2023Article
- Research Topics of the Bioinformatics of Gene Regulation.International journal of molecular sciences · 2023Article
- Cell type-specific interpretation of noncoding variants using deep learning-based methods.GigaScience · 2023Article
- Function and Evolution of the Loop Extrusion Machinery in Animals.International journal of molecular sciences · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genome architecture plays a pivotal role in gene regulation. The use of high-throughput methods for chromatin profiling and 3-D interaction mapping provide rich experimental data sets describing genome organization and dynamics. These data challenge development of new models and algorithms connecting genome architecture with epigenetic marks. In this review, we describe how chromatin architecture could be reconstructed from epigenetic data using biophysical or statistical approaches. We discuss the applicability and limitations of these methods for understanding the mechanisms of chromatin organization. We also highlight the emergence of new predictive approaches for scoring effects of structural variations in human cells.
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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 Socratic graph.