ReviewComputational and structural biotechnology journal2021
Application of Hi-C and other omics data analysis in human cancer and cell differentiation research.
Review in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
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
13 citing papers in PubMed.
- Deep learning application for genomic data analysis.BMB reports · 2026Review
- HiC4D-SPOT: a spatiotemporal outlier detection tool for Hi-C data.Briefings in bioinformatics · 2025Article
- Review
- DconnLoop: a deep learning model for predicting chromatin loops based on multi-source data integration.BMC bioinformatics · 2025Article
- Comparing chromatin contact maps at scale: methods and insights.Nature methods · 2025Article
- HiCrayon reveals distinct layers of multi-state 3D chromatin organization.NAR genomics and bioinformatics · 2024Article
- The chromatin tapestry as a framework for neurodevelopment.Genome research · 2024Review
- HiCrayon reveals distinct layers of multi-state 3D chromatin organization.bioRxiv : the preprint server for biology · 2024Article
- Hi-C, a chromatin 3D structure technique advancing the functional genomics of immune cells.Frontiers in genetics · 2024Review
- Transcription factor-mediated direct cellular reprogramming yields cell-type specific DNA methylation signature.Scientific reports · 2023Article
- 3D genome organization links non-coding disease-associated variants to genes.Frontiers in cell and developmental biology · 2022Review
- Productive visualization of high-throughput sequencing data using the SeqCode open portable platform.Scientific reports · 2021Article
- Non-Coding Variants in Cancer: Mechanistic Insights and Clinical Potential for Personalized Medicine.Non-coding RNA · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the development of 3C (chromosome conformation capture) and its derivative technology Hi-C (High-throughput chromosome conformation capture) research, the study of the spatial structure of the genomic sequence in the nucleus helps researchers understand the functions of biological processes such as gene transcription, replication, repair, and regulation. In this paper, we first introduce the research background and purpose of Hi-C data visualization analysis. After that, we discuss the Hi-C data analysis methods from genome 3D structure, A/B compartment, TADs (topologically associated domain), and loop detection. We also discuss how to apply genome visualization technologies to the identification of chromosome feature structures. We continue with a review of correlation analysis differences among multi-omics data, and how to apply Hi-C and other omics data analysis into cancer and cell differentiation research. Finally, we summarize the various problems in joint analyses based on Hi-C and other multi-omics data. We believe this review can help researchers better understand the progress and applications of 3D genome technology.
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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.