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Computational Biology Solutions to Identify Enhancers-target Gene Pairs
Enhancers are non-coding regulatory elements that are distant from their target gene. Their characterization still remains elusive especially due to challenges in achieving a comprehensive pairing of enhancers and target genes. A number of computational biology solutions have been proposed to addres...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2019
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6611831/ https://www.ncbi.nlm.nih.gov/pubmed/31316726 http://dx.doi.org/10.1016/j.csbj.2019.06.012 |
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author | Hariprakash, Judith Mary Ferrari, Francesco |
author_facet | Hariprakash, Judith Mary Ferrari, Francesco |
author_sort | Hariprakash, Judith Mary |
collection | PubMed |
description | Enhancers are non-coding regulatory elements that are distant from their target gene. Their characterization still remains elusive especially due to challenges in achieving a comprehensive pairing of enhancers and target genes. A number of computational biology solutions have been proposed to address this problem leveraging the increasing availability of functional genomics data and the improved mechanistic understanding of enhancer action. In this review we focus on computational methods for genome-wide definition of enhancer-target gene pairs. We outline the different classes of methods, as well as their main advantages and limitations. The types of information integrated by each method, along with details on their applicability are presented and discussed. We especially highlight the technical challenges that are still unresolved and hamper the effective achievement of a satisfactory and comprehensive solution. We expect this field will keep evolving in the coming years due to the ever-growing availability of data and increasing insights into enhancers crucial role in regulating genome functionality. |
format | Online Article Text |
id | pubmed-6611831 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-66118312019-07-17 Computational Biology Solutions to Identify Enhancers-target Gene Pairs Hariprakash, Judith Mary Ferrari, Francesco Comput Struct Biotechnol J Review Article Enhancers are non-coding regulatory elements that are distant from their target gene. Their characterization still remains elusive especially due to challenges in achieving a comprehensive pairing of enhancers and target genes. A number of computational biology solutions have been proposed to address this problem leveraging the increasing availability of functional genomics data and the improved mechanistic understanding of enhancer action. In this review we focus on computational methods for genome-wide definition of enhancer-target gene pairs. We outline the different classes of methods, as well as their main advantages and limitations. The types of information integrated by each method, along with details on their applicability are presented and discussed. We especially highlight the technical challenges that are still unresolved and hamper the effective achievement of a satisfactory and comprehensive solution. We expect this field will keep evolving in the coming years due to the ever-growing availability of data and increasing insights into enhancers crucial role in regulating genome functionality. Research Network of Computational and Structural Biotechnology 2019-06-14 /pmc/articles/PMC6611831/ /pubmed/31316726 http://dx.doi.org/10.1016/j.csbj.2019.06.012 Text en © 2019 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Review Article Hariprakash, Judith Mary Ferrari, Francesco Computational Biology Solutions to Identify Enhancers-target Gene Pairs |
title | Computational Biology Solutions to Identify Enhancers-target Gene Pairs |
title_full | Computational Biology Solutions to Identify Enhancers-target Gene Pairs |
title_fullStr | Computational Biology Solutions to Identify Enhancers-target Gene Pairs |
title_full_unstemmed | Computational Biology Solutions to Identify Enhancers-target Gene Pairs |
title_short | Computational Biology Solutions to Identify Enhancers-target Gene Pairs |
title_sort | computational biology solutions to identify enhancers-target gene pairs |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6611831/ https://www.ncbi.nlm.nih.gov/pubmed/31316726 http://dx.doi.org/10.1016/j.csbj.2019.06.012 |
work_keys_str_mv | AT hariprakashjudithmary computationalbiologysolutionstoidentifyenhancerstargetgenepairs AT ferrarifrancesco computationalbiologysolutionstoidentifyenhancerstargetgenepairs |