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Chromatin Hubs: A biological and computational outlook

This review discusses our current understanding of chromatin biology and bioinformatics under the unifying concept of “chromatin hubs.” The first part reviews the biology of chromatin hubs, including chromatin–chromatin interaction hubs, chromatin hubs at the nuclear periphery, hubs around macromole...

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Detalles Bibliográficos
Autores principales: Mora, Antonio, Huang, Xiaowei, Jauhari, Shaurya, Jiang, Qin, Li, Xuri
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9304431/
https://www.ncbi.nlm.nih.gov/pubmed/35891791
http://dx.doi.org/10.1016/j.csbj.2022.07.002
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author Mora, Antonio
Huang, Xiaowei
Jauhari, Shaurya
Jiang, Qin
Li, Xuri
author_facet Mora, Antonio
Huang, Xiaowei
Jauhari, Shaurya
Jiang, Qin
Li, Xuri
author_sort Mora, Antonio
collection PubMed
description This review discusses our current understanding of chromatin biology and bioinformatics under the unifying concept of “chromatin hubs.” The first part reviews the biology of chromatin hubs, including chromatin–chromatin interaction hubs, chromatin hubs at the nuclear periphery, hubs around macromolecules such as RNA polymerase or lncRNAs, and hubs around nuclear bodies such as the nucleolus or nuclear speckles. The second part reviews existing computational methods, including enhancer–promoter interaction prediction, network analysis, chromatin domain callers, transcription factory predictors, and multi-way interaction analysis. We introduce an integrated model that makes sense of the existing evidence. Understanding chromatin hubs may allow us (i) to explain long-unsolved biological questions such as interaction specificity and redundancy of mechanisms, (ii) to develop more realistic kinetic and functional predictions, and (iii) to explain the etiology of genomic disease.
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spelling pubmed-93044312022-07-25 Chromatin Hubs: A biological and computational outlook Mora, Antonio Huang, Xiaowei Jauhari, Shaurya Jiang, Qin Li, Xuri Comput Struct Biotechnol J Review This review discusses our current understanding of chromatin biology and bioinformatics under the unifying concept of “chromatin hubs.” The first part reviews the biology of chromatin hubs, including chromatin–chromatin interaction hubs, chromatin hubs at the nuclear periphery, hubs around macromolecules such as RNA polymerase or lncRNAs, and hubs around nuclear bodies such as the nucleolus or nuclear speckles. The second part reviews existing computational methods, including enhancer–promoter interaction prediction, network analysis, chromatin domain callers, transcription factory predictors, and multi-way interaction analysis. We introduce an integrated model that makes sense of the existing evidence. Understanding chromatin hubs may allow us (i) to explain long-unsolved biological questions such as interaction specificity and redundancy of mechanisms, (ii) to develop more realistic kinetic and functional predictions, and (iii) to explain the etiology of genomic disease. Research Network of Computational and Structural Biotechnology 2022-07-05 /pmc/articles/PMC9304431/ /pubmed/35891791 http://dx.doi.org/10.1016/j.csbj.2022.07.002 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Mora, Antonio
Huang, Xiaowei
Jauhari, Shaurya
Jiang, Qin
Li, Xuri
Chromatin Hubs: A biological and computational outlook
title Chromatin Hubs: A biological and computational outlook
title_full Chromatin Hubs: A biological and computational outlook
title_fullStr Chromatin Hubs: A biological and computational outlook
title_full_unstemmed Chromatin Hubs: A biological and computational outlook
title_short Chromatin Hubs: A biological and computational outlook
title_sort chromatin hubs: a biological and computational outlook
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9304431/
https://www.ncbi.nlm.nih.gov/pubmed/35891791
http://dx.doi.org/10.1016/j.csbj.2022.07.002
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