ArticleBriefings in bioinformatics2021
Single-cell Hi-C data analysis: safety in numbers.
Article in Briefings in bioinformatics, 2021. 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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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
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Who cites it
39 citing papers in PubMed.
- ssJSD: A Fusion of Sparsity and Spatial Information for HiC Single-Cell Clustering.bioRxiv : the preprint server for biology · 2026Article
- Origins and consequences of oncogenic 3D chromatin remodelling.Nature reviews. Cancer · 2026Review
- Simultaneous modeling of chromatin conformation changes from multiple single-cell interaction maps with ChromMovie.Genome research · 2026Article
- SCUDDO: an unsupervised clustering algorithm for single-cell Hi-C maps using diagonal diffusion operators.Bioinformatics (Oxford, England) · 2026Article
- Jointly-hic: joint decomposition of contact frequency maps captures salient features of genome architecture across tissues and development.Genome biology · 2026Article
- The 3D genomics of lampbrush chromosomes highlights the role of active transcription in chromatin organization.Nucleic acids research · 2026Article
- A wavelet-based approach generates quantitative, scale-free and hierarchical descriptions of 3D genome structures and new biological insights.PLoS computational biology · 2026Article
- scHiCcompare: An R Package for Differential Analysis of Single-cell Hi-C Data.Journal of molecular biology · 2025Article
- Unicorn: enhancing single-cell Hi-C data with blind super-resolution for 3D genome structure reconstruction.Bioinformatics (Oxford, England) · 2025Article
- Generative inpainting of incomplete Euclidean distance matrices of trajectories generated by a fractional Brownian motion.Scientific reports · 2025Article
- ChromMovie: A Molecular Dynamics Approach for Simultaneous Modeling of Chromatin Conformation Changes from Multiple Single-Cell Hi-C Maps.bioRxiv : the preprint server for biology · 2025Article
- Review
- Chromatin structures from integrated AI and polymer physics model.PLoS computational biology · 2025Article
- Article
- ScHiCAtt: Enhancing single-cell Hi-C data resolution using attention-based models.Computational and structural biotechnology journal · 2025Article
- Single-Cell Hi-C Analysis Workflow with Pairtools.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Advancements and future directions in single-cell Hi-C based 3D chromatin modeling.Computational and structural biotechnology journal · 2024Review
- ChromaFold predicts the 3D contact map from single-cell chromatin accessibility.Nature communications · 2024Article
- Enhlink infers distal and context-specific enhancer-promoter linkages.Genome biology · 2024Article
- SnapHiC-G: identifying long-range enhancer-promoter interactions from single-cell Hi-C data via a global background model.Briefings in bioinformatics · 2024Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Over the past decade, genome-wide assays for chromatin interactions in single cells have enabled the study of individual nuclei at unprecedented resolution and throughput. Current chromosome conformation capture techniques survey contacts for up to tens of thousands of individual cells, improving our understanding of genome function in 3D. However, these methods recover a small fraction of all contacts in single cells, requiring specialised processing of sparse interactome data. In this review, we highlight recent advances in methods for the interpretation of single-cell genomic contacts. After discussing the strengths and limitations of these methods, we outline frontiers for future development in this rapidly moving field.
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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.