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GREG-studying transcriptional regulation using integrative graph databases.
Mei, Songqing; Huang, Xiaowei; Xie, Chengshu; Mora, Antonio.
Afiliação
  • Mei S; School of Basic Medical Sciences, Guangzhou Medical University, Panyu Campus of Guangzhou Medical University, Xinzao, 511436 Guangzhou, P.R. China.
  • Huang X; Joint School of Life Sciences, Guangzhou Medical University and Guangzhou Institutes of Biomedicine and Health (Chinese Academy of Sciences), Panyu Campus of Guangzhou Medical University, Xinzao, 511436 Guangzhou, P.R. China.
  • Xie C; Joint School of Life Sciences, Guangzhou Medical University and Guangzhou Institutes of Biomedicine and Health (Chinese Academy of Sciences), Panyu Campus of Guangzhou Medical University, Xinzao, 511436 Guangzhou, P.R. China.
  • Mora A; Joint School of Life Sciences, Guangzhou Medical University and Guangzhou Institutes of Biomedicine and Health (Chinese Academy of Sciences), Panyu Campus of Guangzhou Medical University, Xinzao, 511436 Guangzhou, P.R. China.
Database (Oxford) ; 20202020 01 01.
Article em En | MEDLINE | ID: mdl-32055858
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/.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Fatores de Transcrição / Sistemas de Gerenciamento de Base de Dados / Regulação da Expressão Gênica / Genômica / Bases de Dados Genéticas Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Fatores de Transcrição / Sistemas de Gerenciamento de Base de Dados / Regulação da Expressão Gênica / Genômica / Bases de Dados Genéticas Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article