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Aging Atlas: a multi-omics database for aging biology
Organismal aging is driven by interconnected molecular changes encompassing internal and extracellular factors. Combinational analysis of high-throughput ‘multi-omics’ datasets (gathering information from genomics, epigenomics, transcriptomics, proteomics, metabolomics and pharmacogenomics), at eith...
Formato: | Online Artículo Texto |
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Lenguaje: | English |
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Oxford University Press
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779027/ https://www.ncbi.nlm.nih.gov/pubmed/33119753 http://dx.doi.org/10.1093/nar/gkaa894 |
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collection | PubMed |
description | Organismal aging is driven by interconnected molecular changes encompassing internal and extracellular factors. Combinational analysis of high-throughput ‘multi-omics’ datasets (gathering information from genomics, epigenomics, transcriptomics, proteomics, metabolomics and pharmacogenomics), at either populational or single-cell levels, can provide a multi-dimensional, integrated profile of the heterogeneous aging process with unprecedented throughput and detail. These new strategies allow for the exploration of the molecular profile and regulatory status of gene expression during aging, and in turn, facilitate the development of new aging interventions. With a continually growing volume of valuable aging-related data, it is necessary to establish an open and integrated database to support a wide spectrum of aging research. The Aging Atlas database aims to provide a wide range of life science researchers with valuable resources that allow access to a large-scale of gene expression and regulation datasets created by various high-throughput omics technologies. The current implementation includes five modules: transcriptomics (RNA-seq), single-cell transcriptomics (scRNA-seq), epigenomics (ChIP-seq), proteomics (protein–protein interaction), and pharmacogenomics (geroprotective compounds). Aging Atlas provides user-friendly functionalities to explore age-related changes in gene expression, as well as raw data download services. Aging Atlas is freely available at https://bigd.big.ac.cn/aging/index. |
format | Online Article Text |
id | pubmed-7779027 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-77790272021-01-07 Aging Atlas: a multi-omics database for aging biology Nucleic Acids Res Database Issue Organismal aging is driven by interconnected molecular changes encompassing internal and extracellular factors. Combinational analysis of high-throughput ‘multi-omics’ datasets (gathering information from genomics, epigenomics, transcriptomics, proteomics, metabolomics and pharmacogenomics), at either populational or single-cell levels, can provide a multi-dimensional, integrated profile of the heterogeneous aging process with unprecedented throughput and detail. These new strategies allow for the exploration of the molecular profile and regulatory status of gene expression during aging, and in turn, facilitate the development of new aging interventions. With a continually growing volume of valuable aging-related data, it is necessary to establish an open and integrated database to support a wide spectrum of aging research. The Aging Atlas database aims to provide a wide range of life science researchers with valuable resources that allow access to a large-scale of gene expression and regulation datasets created by various high-throughput omics technologies. The current implementation includes five modules: transcriptomics (RNA-seq), single-cell transcriptomics (scRNA-seq), epigenomics (ChIP-seq), proteomics (protein–protein interaction), and pharmacogenomics (geroprotective compounds). Aging Atlas provides user-friendly functionalities to explore age-related changes in gene expression, as well as raw data download services. Aging Atlas is freely available at https://bigd.big.ac.cn/aging/index. Oxford University Press 2020-10-29 /pmc/articles/PMC7779027/ /pubmed/33119753 http://dx.doi.org/10.1093/nar/gkaa894 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Database Issue Aging Atlas: a multi-omics database for aging biology |
title | Aging Atlas: a multi-omics database for aging biology |
title_full | Aging Atlas: a multi-omics database for aging biology |
title_fullStr | Aging Atlas: a multi-omics database for aging biology |
title_full_unstemmed | Aging Atlas: a multi-omics database for aging biology |
title_short | Aging Atlas: a multi-omics database for aging biology |
title_sort | aging atlas: a multi-omics database for aging biology |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779027/ https://www.ncbi.nlm.nih.gov/pubmed/33119753 http://dx.doi.org/10.1093/nar/gkaa894 |
work_keys_str_mv | AT agingatlasamultiomicsdatabaseforagingbiology |