ArticleJournal of the American Statistical Association2011
Modeling Three-Dimensional Chromosome Structures Using Gene Expression Data.
Article in Journal of the American Statistical Association, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- scHiCSRS: a self-representation smoothing method with Gaussian mixture model for imputing single cell Hi-C data.BMC bioinformatics · 2025Article
- HiCImpute: A Bayesian hierarchical model for identifying structural zeros and enhancing single cell Hi-C data.PLoS computational biology · 2022Article
- Are dropout imputation methods for scRNA-seq effective for scHi-C data?Briefings in bioinformatics · 2021Article
- Elucidating the Influence of Chromosomal Architecture on Transcriptional Regulation in Prokaryotes - Observing Strong Local Effects of Nucleoid Structure on Gene Regulation.Frontiers in microbiology · 2020Article
- A BAYESIAN MARK INTERACTION MODEL FOR ANALYSIS OF TUMOR PATHOLOGY IMAGES.The annals of applied statistics · 2019Article
- A Bayesian latent variable approach to aggregation of partial and top-ranked lists in genomic studies.Statistics in medicine · 2018Article
- Functional Parallel Factor Analysis for Functions of One- and Two-dimensional Arguments.Psychometrika · 2018Article
- Impact of Chromosomal Architecture on the Function and Evolution of Bacterial Genomes.Frontiers in microbiology · 2018Review
- Integrative analysis of gene expression and methylation data for breast cancer cell lines.BioData mining · 2018Article
- Perturbed states of the bacterial chromosome: a thymineless death case study.Frontiers in microbiology · 2015Review
- Ensemble-based network aggregation improves the accuracy of gene network reconstruction.PloS one · 2014Article
- PreCisIon: PREdiction of CIS-regulatory elements improved by gene's positION.Nucleic acids research · 2013Article
- Article
- Inferring Spatial Organization of Individual Topologically Associated Domains via Piecewise Helical Model.IEEE/ACM transactions on computational biology and bioinformaticsArticle
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Recent genomic studies have shown that significant chromosomal spatial correlation exists in gene expression of many organisms. Interestingly, coexpression has been observed among genes separated by a fixed interval in specific regions of a chromosome chain, which is likely caused by three-dimensional (3D) chromosome folding structures. Modeling such spatial correlation explicitly may lead to essential understandings of 3D chromosome structures and their roles in transcriptional regulation. In this paper, we explore chromosomal spatial correlation induced by 3D chromosome structures, and propose a hierarchical Bayesian method based on helical structures to formally model and incorporate the correlation into the analysis of gene expression microarray data. It is the first study to quantify and infer 3D chromosome structures in vivo using expression microarrays. Simulation studies show computing feasibility of the proposed method and that, under the assumption of helical chromosome structures, it can lead to precise estimation of structural parameters and gene expression levels. Real data applications demonstrate an intriguing biological phenomenon that functionally associated genes, which are far apart along the chromosome chain, are brought into physical proximity by chromosomal folding in 3D space to facilitate their coexpression. It leads to important biological insight into relationship between chromosome structure and function.
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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.