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GRAND: a database of gene regulatory network models across human conditions
Gene regulation plays a fundamental role in shaping tissue identity, function, and response to perturbation. Regulatory processes are controlled by complex networks of interacting elements, including transcription factors, miRNAs and their target genes. The structure of these networks helps to deter...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8728257/ https://www.ncbi.nlm.nih.gov/pubmed/34508353 http://dx.doi.org/10.1093/nar/gkab778 |
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author | Ben Guebila, Marouen Lopes-Ramos, Camila M Weighill, Deborah Sonawane, Abhijeet Rajendra Burkholz, Rebekka Shamsaei, Behrouz Platig, John Glass, Kimberly Kuijjer, Marieke L Quackenbush, John |
author_facet | Ben Guebila, Marouen Lopes-Ramos, Camila M Weighill, Deborah Sonawane, Abhijeet Rajendra Burkholz, Rebekka Shamsaei, Behrouz Platig, John Glass, Kimberly Kuijjer, Marieke L Quackenbush, John |
author_sort | Ben Guebila, Marouen |
collection | PubMed |
description | Gene regulation plays a fundamental role in shaping tissue identity, function, and response to perturbation. Regulatory processes are controlled by complex networks of interacting elements, including transcription factors, miRNAs and their target genes. The structure of these networks helps to determine phenotypes and can ultimately influence the development of disease or response to therapy. We developed GRAND (https://grand.networkmedicine.org) as a database for computationally-inferred, context-specific gene regulatory network models that can be compared between biological states, or used to predict which drugs produce changes in regulatory network structure. The database includes 12 468 genome-scale networks covering 36 human tissues, 28 cancers, 1378 unperturbed cell lines, as well as 173 013 TF and gene targeting scores for 2858 small molecule-induced cell line perturbation paired with phenotypic information. GRAND allows the networks to be queried using phenotypic information and visualized using a variety of interactive tools. In addition, it includes a web application that matches disease states to potentially therapeutic small molecule drugs using regulatory network properties. |
format | Online Article Text |
id | pubmed-8728257 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-87282572022-01-05 GRAND: a database of gene regulatory network models across human conditions Ben Guebila, Marouen Lopes-Ramos, Camila M Weighill, Deborah Sonawane, Abhijeet Rajendra Burkholz, Rebekka Shamsaei, Behrouz Platig, John Glass, Kimberly Kuijjer, Marieke L Quackenbush, John Nucleic Acids Res Database Issue Gene regulation plays a fundamental role in shaping tissue identity, function, and response to perturbation. Regulatory processes are controlled by complex networks of interacting elements, including transcription factors, miRNAs and their target genes. The structure of these networks helps to determine phenotypes and can ultimately influence the development of disease or response to therapy. We developed GRAND (https://grand.networkmedicine.org) as a database for computationally-inferred, context-specific gene regulatory network models that can be compared between biological states, or used to predict which drugs produce changes in regulatory network structure. The database includes 12 468 genome-scale networks covering 36 human tissues, 28 cancers, 1378 unperturbed cell lines, as well as 173 013 TF and gene targeting scores for 2858 small molecule-induced cell line perturbation paired with phenotypic information. GRAND allows the networks to be queried using phenotypic information and visualized using a variety of interactive tools. In addition, it includes a web application that matches disease states to potentially therapeutic small molecule drugs using regulatory network properties. Oxford University Press 2021-09-11 /pmc/articles/PMC8728257/ /pubmed/34508353 http://dx.doi.org/10.1093/nar/gkab778 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Database Issue Ben Guebila, Marouen Lopes-Ramos, Camila M Weighill, Deborah Sonawane, Abhijeet Rajendra Burkholz, Rebekka Shamsaei, Behrouz Platig, John Glass, Kimberly Kuijjer, Marieke L Quackenbush, John GRAND: a database of gene regulatory network models across human conditions |
title | GRAND: a database of gene regulatory network models across human conditions |
title_full | GRAND: a database of gene regulatory network models across human conditions |
title_fullStr | GRAND: a database of gene regulatory network models across human conditions |
title_full_unstemmed | GRAND: a database of gene regulatory network models across human conditions |
title_short | GRAND: a database of gene regulatory network models across human conditions |
title_sort | grand: a database of gene regulatory network models across human conditions |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8728257/ https://www.ncbi.nlm.nih.gov/pubmed/34508353 http://dx.doi.org/10.1093/nar/gkab778 |
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