ArticlePloS one2013
The properties of genome conformation and spatial gene interaction and regulation networks of normal and malignant human cell types.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 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.
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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
23 citing papers in PubMed.
- ENT3C: an entropy-based similarity measure for Hi-C and micro-C derived contact matrices.NAR genomics and bioinformatics · 2024Article
- Network-level enrichment provides a framework for biological interpretation of machine learning results.Network neuroscience (Cambridge, Mass.) · 2024Article
- A graph neural network-based interpretable framework reveals a novel DNA fragility-associated chromatin structural unit.Genome biology · 2023Article
- Article
- Integrative Analysis of Genome, 3D Genome, and Transcriptome Alterations of Clinical Lung Cancer Samples.Genomics, proteomics & bioinformatics · 2021Article
- A computational framework for identifying the transcription factors involved in enhancer-promoter loop formation.Molecular therapy. Nucleic acids · 2021Article
- normGAM: an R package to remove systematic biases in genome architecture mapping data.BMC genomics · 2019Article
- Exploring the 2D and 3D structural properties of topologically associating domains.BMC bioinformatics · 2019Article
- Suppression of a Prolyl 4 Hydroxylase Results in Delayed Abscission of Overripe Tomato Fruits.Frontiers in plant science · 2019Article
- Reconstructing high-resolution chromosome three-dimensional structures by Hi-C complex networks.BMC bioinformatics · 2018Article
- Integrative detection and analysis of structural variation in cancer genomes.Nature genetics · 2018Article
- A maximum likelihood algorithm for reconstructing 3D structures of human chromosomes from chromosomal contact data.BMC genomics · 2018Article
- Novel insights into chromosomal conformations in cancer.Molecular cancer · 2017Review
- ClusterTAD: an unsupervised machine learning approach to detecting topologically associated domains of chromosomes from Hi-C data.BMC bioinformatics · 2017Article
- Predicting DNA Methylation State of CpG Dinucleotide Using Genome Topological Features and Deep Networks.Scientific reports · 2016Article
- Integrated protein function prediction by mining function associations, sequences, and protein-protein and gene-gene interaction networks.Methods (San Diego, Calif.) · 2016Article
- Deciphering the association between gene function and spatial gene-gene interactions in 3D human genome conformation.BMC genomics · 2015Article
- Iterative reconstruction of three-dimensional models of human chromosomes from chromosomal contact data.BMC bioinformatics · 2015Article
- Male-biased aganglionic megacolon in the TashT mouse line due to perturbation of silencer elements in a large gene desert of chromosome 10.PLoS genetics · 2015Article
- Integrating multi-omic features exploiting Chromosome Conformation Capture data.Frontiers in genetics · 2015Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
The spatial conformation of a genome plays an important role in the long-range regulation of genome-wide gene expression and methylation, but has not been extensively studied due to lack of genome conformation data. The recently developed chromosome conformation capturing techniques such as the Hi-C method empowered by next generation sequencing can generate unbiased, large-scale, high-resolution chromosomal interaction (contact) data, providing an unprecedented opportunity to investigate the spatial structure of a genome and its applications in gene regulation, genomics, epigenetics, and cell biology. In this work, we conducted a comprehensive, large-scale computational analysis of this new stream of genome conformation data generated for three different human leukemia cells or cell lines by the Hi-C technique. We developed and applied a set of bioinformatics methods to reliably generate spatial chromosomal contacts from high-throughput sequencing data and to effectively use them to study the properties of the genome structures in one-dimension (1D) and two-dimension (2D). Our analysis demonstrates that Hi-C data can be effectively applied to study tissue-specific genome conformation, chromosome-chromosome interaction, chromosomal translocations, and spatial gene-gene interaction and regulation in a three-dimensional genome of primary tumor cells. Particularly, for the first time, we constructed genome-scale spatial gene-gene interaction network, transcription factor binding site (TFBS) - TFBS interaction network, and TFBS-gene interaction network from chromosomal contact information. Remarkably, all these networks possess the properties of scale-free modular networks.
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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.