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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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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/ |
format | Online Article Text |
id | pubmed-7018612 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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