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DBTSS/DBKERO for integrated analysis of transcriptional regulation
DBTSS (Database of Transcriptional Start Sites)/DBKERO (Database of Kashiwa Encyclopedia for human genome mutations in Regulatory regions and their Omics contexts) is the database originally initiated with the information of transcriptional start sites and their upstream transcriptional regulatory r...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5753362/ https://www.ncbi.nlm.nih.gov/pubmed/29126224 http://dx.doi.org/10.1093/nar/gkx1001 |
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author | Suzuki, Ayako Kawano, Shin Mitsuyama, Toutai Suyama, Mikita Kanai, Yae Shirahige, Katsuhiko Sasaki, Hiroyuki Tokunaga, Katsushi Tsuchihara, Katsuya Sugano, Sumio Nakai, Kenta Suzuki, Yutaka |
author_facet | Suzuki, Ayako Kawano, Shin Mitsuyama, Toutai Suyama, Mikita Kanai, Yae Shirahige, Katsuhiko Sasaki, Hiroyuki Tokunaga, Katsushi Tsuchihara, Katsuya Sugano, Sumio Nakai, Kenta Suzuki, Yutaka |
author_sort | Suzuki, Ayako |
collection | PubMed |
description | DBTSS (Database of Transcriptional Start Sites)/DBKERO (Database of Kashiwa Encyclopedia for human genome mutations in Regulatory regions and their Omics contexts) is the database originally initiated with the information of transcriptional start sites and their upstream transcriptional regulatory regions. In recent years, we updated the database to assist users to elucidate biological relevance of the human genome variations or somatic mutations in cancers which may affect the transcriptional regulation. In this update, we facilitate interpretations of disease associated genomic variation, using the Japanese population as a model case. We enriched the genomic variation dataset consisting of the 13,368 individuals collected for various genome-wide association studies and the reference epigenome information in the surrounding regions using a total of 455 epigenome datasets (four tissue types from 67 healthy individuals) collected for the International Human Epigenome Consortium (IHEC). The data directly obtained from the clinical samples was associated with that obtained from various model systems, such as the drug perturbation datasets using cultured cancer cells. Furthermore, we incorporated the results obtained using the newly developed analytical methods, Nanopore/10x Genomics long-read sequencing of the human genome and single cell analyses. The database is made publicly accessible at the URL (http://dbtss.hgc.jp/). |
format | Online Article Text |
id | pubmed-5753362 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-57533622018-01-05 DBTSS/DBKERO for integrated analysis of transcriptional regulation Suzuki, Ayako Kawano, Shin Mitsuyama, Toutai Suyama, Mikita Kanai, Yae Shirahige, Katsuhiko Sasaki, Hiroyuki Tokunaga, Katsushi Tsuchihara, Katsuya Sugano, Sumio Nakai, Kenta Suzuki, Yutaka Nucleic Acids Res Database Issue DBTSS (Database of Transcriptional Start Sites)/DBKERO (Database of Kashiwa Encyclopedia for human genome mutations in Regulatory regions and their Omics contexts) is the database originally initiated with the information of transcriptional start sites and their upstream transcriptional regulatory regions. In recent years, we updated the database to assist users to elucidate biological relevance of the human genome variations or somatic mutations in cancers which may affect the transcriptional regulation. In this update, we facilitate interpretations of disease associated genomic variation, using the Japanese population as a model case. We enriched the genomic variation dataset consisting of the 13,368 individuals collected for various genome-wide association studies and the reference epigenome information in the surrounding regions using a total of 455 epigenome datasets (four tissue types from 67 healthy individuals) collected for the International Human Epigenome Consortium (IHEC). The data directly obtained from the clinical samples was associated with that obtained from various model systems, such as the drug perturbation datasets using cultured cancer cells. Furthermore, we incorporated the results obtained using the newly developed analytical methods, Nanopore/10x Genomics long-read sequencing of the human genome and single cell analyses. The database is made publicly accessible at the URL (http://dbtss.hgc.jp/). Oxford University Press 2018-01-04 2017-11-08 /pmc/articles/PMC5753362/ /pubmed/29126224 http://dx.doi.org/10.1093/nar/gkx1001 Text en © The Author(s) 2017. 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 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 Suzuki, Ayako Kawano, Shin Mitsuyama, Toutai Suyama, Mikita Kanai, Yae Shirahige, Katsuhiko Sasaki, Hiroyuki Tokunaga, Katsushi Tsuchihara, Katsuya Sugano, Sumio Nakai, Kenta Suzuki, Yutaka DBTSS/DBKERO for integrated analysis of transcriptional regulation |
title | DBTSS/DBKERO for integrated analysis of transcriptional regulation |
title_full | DBTSS/DBKERO for integrated analysis of transcriptional regulation |
title_fullStr | DBTSS/DBKERO for integrated analysis of transcriptional regulation |
title_full_unstemmed | DBTSS/DBKERO for integrated analysis of transcriptional regulation |
title_short | DBTSS/DBKERO for integrated analysis of transcriptional regulation |
title_sort | dbtss/dbkero for integrated analysis of transcriptional regulation |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5753362/ https://www.ncbi.nlm.nih.gov/pubmed/29126224 http://dx.doi.org/10.1093/nar/gkx1001 |
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