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Xenbase: deep integration of GEO & SRA RNA-seq and ChIP-seq data in a model organism database
Xenbase (www.xenbase.org) is a knowledge base for researchers and biomedical scientists that employ the amphibian Xenopus as a model organism in biomedical research to gain a deeper understanding of developmental and disease processes. Through expert curation and automated data provisioning from var...
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/PMC7145613/ https://www.ncbi.nlm.nih.gov/pubmed/31733057 http://dx.doi.org/10.1093/nar/gkz933 |
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author | Fortriede, Joshua D Pells, Troy J Chu, Stanley Chaturvedi, Praneet Wang, DongZhuo Fisher, Malcom E James-Zorn, Christina Wang, Ying Nenni, Mardi J Burns, Kevin A Lotay, Vaneet S Ponferrada, Virgilio G Karimi, Kamran Zorn, Aaron M Vize, Peter D |
author_facet | Fortriede, Joshua D Pells, Troy J Chu, Stanley Chaturvedi, Praneet Wang, DongZhuo Fisher, Malcom E James-Zorn, Christina Wang, Ying Nenni, Mardi J Burns, Kevin A Lotay, Vaneet S Ponferrada, Virgilio G Karimi, Kamran Zorn, Aaron M Vize, Peter D |
author_sort | Fortriede, Joshua D |
collection | PubMed |
description | Xenbase (www.xenbase.org) is a knowledge base for researchers and biomedical scientists that employ the amphibian Xenopus as a model organism in biomedical research to gain a deeper understanding of developmental and disease processes. Through expert curation and automated data provisioning from various sources Xenbase strives to integrate the body of knowledge on Xenopus genomics and biology together with the visualization of biologically significant interactions. Most current studies utilize next generation sequencing (NGS) but until now the results of different experiments were difficult to compare and not integrated with other Xenbase content. Xenbase has developed a suite of tools, interfaces and data processing pipelines that transforms NCBI Gene Expression Omnibus (GEO) NGS content into deeply integrated gene expression and chromatin data, mapping all aligned reads to the most recent genome builds. This content can be queried and visualized via multiple tools and also provides the basis for future automated ‘gene expression as a phenotype’ and gene regulatory network analyses. |
format | Online Article Text |
id | pubmed-7145613 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-71456132020-04-13 Xenbase: deep integration of GEO & SRA RNA-seq and ChIP-seq data in a model organism database Fortriede, Joshua D Pells, Troy J Chu, Stanley Chaturvedi, Praneet Wang, DongZhuo Fisher, Malcom E James-Zorn, Christina Wang, Ying Nenni, Mardi J Burns, Kevin A Lotay, Vaneet S Ponferrada, Virgilio G Karimi, Kamran Zorn, Aaron M Vize, Peter D Nucleic Acids Res Database Issue Xenbase (www.xenbase.org) is a knowledge base for researchers and biomedical scientists that employ the amphibian Xenopus as a model organism in biomedical research to gain a deeper understanding of developmental and disease processes. Through expert curation and automated data provisioning from various sources Xenbase strives to integrate the body of knowledge on Xenopus genomics and biology together with the visualization of biologically significant interactions. Most current studies utilize next generation sequencing (NGS) but until now the results of different experiments were difficult to compare and not integrated with other Xenbase content. Xenbase has developed a suite of tools, interfaces and data processing pipelines that transforms NCBI Gene Expression Omnibus (GEO) NGS content into deeply integrated gene expression and chromatin data, mapping all aligned reads to the most recent genome builds. This content can be queried and visualized via multiple tools and also provides the basis for future automated ‘gene expression as a phenotype’ and gene regulatory network analyses. Oxford University Press 2020-01-08 2019-11-16 /pmc/articles/PMC7145613/ /pubmed/31733057 http://dx.doi.org/10.1093/nar/gkz933 Text en © The Author(s) 2019. 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 Fortriede, Joshua D Pells, Troy J Chu, Stanley Chaturvedi, Praneet Wang, DongZhuo Fisher, Malcom E James-Zorn, Christina Wang, Ying Nenni, Mardi J Burns, Kevin A Lotay, Vaneet S Ponferrada, Virgilio G Karimi, Kamran Zorn, Aaron M Vize, Peter D Xenbase: deep integration of GEO & SRA RNA-seq and ChIP-seq data in a model organism database |
title | Xenbase: deep integration of GEO & SRA RNA-seq and ChIP-seq data in a model organism database |
title_full | Xenbase: deep integration of GEO & SRA RNA-seq and ChIP-seq data in a model organism database |
title_fullStr | Xenbase: deep integration of GEO & SRA RNA-seq and ChIP-seq data in a model organism database |
title_full_unstemmed | Xenbase: deep integration of GEO & SRA RNA-seq and ChIP-seq data in a model organism database |
title_short | Xenbase: deep integration of GEO & SRA RNA-seq and ChIP-seq data in a model organism database |
title_sort | xenbase: deep integration of geo & sra rna-seq and chip-seq data in a model organism database |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7145613/ https://www.ncbi.nlm.nih.gov/pubmed/31733057 http://dx.doi.org/10.1093/nar/gkz933 |
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