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Computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles

The exploration of three-dimensional chromatin interaction and organization provides insight into mechanisms underlying gene regulation, cell differentiation and disease development. Advances in chromosome conformation capture technologies, such as high-throughput chromosome conformation capture (Hi...

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Autores principales: Tao, Huan, Li, Hao, Xu, Kang, Hong, Hao, Jiang, Shuai, Du, Guifang, Wang, Junting, Sun, Yu, Huang, Xin, Ding, Yang, Li, Fei, Zheng, Xiaofei, Chen, Hebing, Bo, Xiaochen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8424394/
https://www.ncbi.nlm.nih.gov/pubmed/33454752
http://dx.doi.org/10.1093/bib/bbaa405
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author Tao, Huan
Li, Hao
Xu, Kang
Hong, Hao
Jiang, Shuai
Du, Guifang
Wang, Junting
Sun, Yu
Huang, Xin
Ding, Yang
Li, Fei
Zheng, Xiaofei
Chen, Hebing
Bo, Xiaochen
author_facet Tao, Huan
Li, Hao
Xu, Kang
Hong, Hao
Jiang, Shuai
Du, Guifang
Wang, Junting
Sun, Yu
Huang, Xin
Ding, Yang
Li, Fei
Zheng, Xiaofei
Chen, Hebing
Bo, Xiaochen
author_sort Tao, Huan
collection PubMed
description The exploration of three-dimensional chromatin interaction and organization provides insight into mechanisms underlying gene regulation, cell differentiation and disease development. Advances in chromosome conformation capture technologies, such as high-throughput chromosome conformation capture (Hi-C) and chromatin interaction analysis by paired-end tag (ChIA-PET), have enabled the exploration of chromatin interaction and organization. However, high-resolution Hi-C and ChIA-PET data are only available for a limited number of cell lines, and their acquisition is costly, time consuming, laborious and affected by theoretical limitations. Increasing evidence shows that DNA sequence and epigenomic features are informative predictors of regulatory interaction and chromatin architecture. Based on these features, numerous computational methods have been developed for the prediction of chromatin interaction and organization, whereas they are not extensively applied in biomedical study. A systematical study to summarize and evaluate such methods is still needed to facilitate their application. Here, we summarize 48 computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles, categorize them and compare their performance. Besides, we provide a comprehensive guideline for the selection of suitable methods to predict chromatin interaction and organization based on available data and biological question of interest.
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spelling pubmed-84243942021-09-09 Computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles Tao, Huan Li, Hao Xu, Kang Hong, Hao Jiang, Shuai Du, Guifang Wang, Junting Sun, Yu Huang, Xin Ding, Yang Li, Fei Zheng, Xiaofei Chen, Hebing Bo, Xiaochen Brief Bioinform Method Review The exploration of three-dimensional chromatin interaction and organization provides insight into mechanisms underlying gene regulation, cell differentiation and disease development. Advances in chromosome conformation capture technologies, such as high-throughput chromosome conformation capture (Hi-C) and chromatin interaction analysis by paired-end tag (ChIA-PET), have enabled the exploration of chromatin interaction and organization. However, high-resolution Hi-C and ChIA-PET data are only available for a limited number of cell lines, and their acquisition is costly, time consuming, laborious and affected by theoretical limitations. Increasing evidence shows that DNA sequence and epigenomic features are informative predictors of regulatory interaction and chromatin architecture. Based on these features, numerous computational methods have been developed for the prediction of chromatin interaction and organization, whereas they are not extensively applied in biomedical study. A systematical study to summarize and evaluate such methods is still needed to facilitate their application. Here, we summarize 48 computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles, categorize them and compare their performance. Besides, we provide a comprehensive guideline for the selection of suitable methods to predict chromatin interaction and organization based on available data and biological question of interest. Oxford University Press 2021-01-18 /pmc/articles/PMC8424394/ /pubmed/33454752 http://dx.doi.org/10.1093/bib/bbaa405 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Method Review
Tao, Huan
Li, Hao
Xu, Kang
Hong, Hao
Jiang, Shuai
Du, Guifang
Wang, Junting
Sun, Yu
Huang, Xin
Ding, Yang
Li, Fei
Zheng, Xiaofei
Chen, Hebing
Bo, Xiaochen
Computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles
title Computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles
title_full Computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles
title_fullStr Computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles
title_full_unstemmed Computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles
title_short Computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles
title_sort computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles
topic Method Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8424394/
https://www.ncbi.nlm.nih.gov/pubmed/33454752
http://dx.doi.org/10.1093/bib/bbaa405
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