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GREG—studying transcriptional regulation using integrative graph databases

A gene regulatory process is the result of the concerted action of transcription factors, co-factors, regulatory non-coding RNAs (ncRNAs) and chromatin interactions. Therefore, the combination of protein–DNA, protein–protein, ncRNA–DNA, ncRNA–protein and DNA–DNA data in a single graph database offer...

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Detalles Bibliográficos
Autores principales: Mei, Songqing, Huang, Xiaowei, Xie, Chengshu, Mora, Antonio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7018612/
https://www.ncbi.nlm.nih.gov/pubmed/32055858
http://dx.doi.org/10.1093/database/baz162
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author Mei, Songqing
Huang, Xiaowei
Xie, Chengshu
Mora, Antonio
author_facet Mei, Songqing
Huang, Xiaowei
Xie, Chengshu
Mora, Antonio
author_sort Mei, Songqing
collection PubMed
description A gene regulatory process is the result of the concerted action of transcription factors, co-factors, regulatory non-coding RNAs (ncRNAs) and chromatin interactions. Therefore, the combination of protein–DNA, protein–protein, ncRNA–DNA, ncRNA–protein and DNA–DNA data in a single graph database offers new possibilities regarding generation of biological hypotheses. GREG (The Gene Regulation Graph Database) is an integrative database and web resource that allows the user to visualize and explore the network of all above-mentioned interactions for a query transcription factor, long non-coding RNA, genomic range or DNA annotation, as well as extracting node and interaction information, identifying connected nodes and performing advanced graphical queries directly on the regulatory network, in a simple and efficient way. In this article, we introduce GREG together with some application examples (including exploratory research of Nanog’s regulatory landscape and the etiology of chronic obstructive pulmonary disease), which we use as a demonstration of the advantages of using graph databases in biomedical research. Database URL: https://mora-lab.github.io/projects/greg.html, www.moralab.science/GREG/
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spelling pubmed-70186122020-02-20 GREG—studying transcriptional regulation using integrative graph databases Mei, Songqing Huang, Xiaowei Xie, Chengshu Mora, Antonio Database (Oxford) Original Article A gene regulatory process is the result of the concerted action of transcription factors, co-factors, regulatory non-coding RNAs (ncRNAs) and chromatin interactions. Therefore, the combination of protein–DNA, protein–protein, ncRNA–DNA, ncRNA–protein and DNA–DNA data in a single graph database offers new possibilities regarding generation of biological hypotheses. GREG (The Gene Regulation Graph Database) is an integrative database and web resource that allows the user to visualize and explore the network of all above-mentioned interactions for a query transcription factor, long non-coding RNA, genomic range or DNA annotation, as well as extracting node and interaction information, identifying connected nodes and performing advanced graphical queries directly on the regulatory network, in a simple and efficient way. In this article, we introduce GREG together with some application examples (including exploratory research of Nanog’s regulatory landscape and the etiology of chronic obstructive pulmonary disease), which we use as a demonstration of the advantages of using graph databases in biomedical research. Database URL: https://mora-lab.github.io/projects/greg.html, www.moralab.science/GREG/ Oxford University Press 2020-02-13 /pmc/articles/PMC7018612/ /pubmed/32055858 http://dx.doi.org/10.1093/database/baz162 Text en © The Author(s) 2020. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Mei, Songqing
Huang, Xiaowei
Xie, Chengshu
Mora, Antonio
GREG—studying transcriptional regulation using integrative graph databases
title GREG—studying transcriptional regulation using integrative graph databases
title_full GREG—studying transcriptional regulation using integrative graph databases
title_fullStr GREG—studying transcriptional regulation using integrative graph databases
title_full_unstemmed GREG—studying transcriptional regulation using integrative graph databases
title_short GREG—studying transcriptional regulation using integrative graph databases
title_sort greg—studying transcriptional regulation using integrative graph databases
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7018612/
https://www.ncbi.nlm.nih.gov/pubmed/32055858
http://dx.doi.org/10.1093/database/baz162
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