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BioXpress: an integrated RNA-seq-derived gene expression database for pan-cancer analysis
BioXpress is a gene expression and cancer association database in which the expression levels are mapped to genes using RNA-seq data obtained from The Cancer Genome Atlas, International Cancer Genome Consortium, Expression Atlas and publications. The BioXpress database includes expression data from...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4377087/ https://www.ncbi.nlm.nih.gov/pubmed/25819073 http://dx.doi.org/10.1093/database/bav019 |
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author | Wan, Quan Dingerdissen, Hayley Fan, Yu Gulzar, Naila Pan, Yang Wu, Tsung-Jung Yan, Cheng Zhang, Haichen Mazumder, Raja |
author_facet | Wan, Quan Dingerdissen, Hayley Fan, Yu Gulzar, Naila Pan, Yang Wu, Tsung-Jung Yan, Cheng Zhang, Haichen Mazumder, Raja |
author_sort | Wan, Quan |
collection | PubMed |
description | BioXpress is a gene expression and cancer association database in which the expression levels are mapped to genes using RNA-seq data obtained from The Cancer Genome Atlas, International Cancer Genome Consortium, Expression Atlas and publications. The BioXpress database includes expression data from 64 cancer types, 6361 patients and 17 469 genes with 9513 of the genes displaying differential expression between tumor and normal samples. In addition to data directly retrieved from RNA-seq data repositories, manual biocuration of publications supplements the available cancer association annotations in the database. All cancer types are mapped to Disease Ontology terms to facilitate a uniform pan-cancer analysis. The BioXpress database is easily searched using HUGO Gene Nomenclature Committee gene symbol, UniProtKB/RefSeq accession or, alternatively, can be queried by cancer type with specified significance filters. This interface along with availability of pre-computed downloadable files containing differentially expressed genes in multiple cancers enables straightforward retrieval and display of a broad set of cancer-related genes. Database URL: http://hive.biochemistry.gwu.edu/tools/bioxpress |
format | Online Article Text |
id | pubmed-4377087 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-43770872015-06-26 BioXpress: an integrated RNA-seq-derived gene expression database for pan-cancer analysis Wan, Quan Dingerdissen, Hayley Fan, Yu Gulzar, Naila Pan, Yang Wu, Tsung-Jung Yan, Cheng Zhang, Haichen Mazumder, Raja Database (Oxford) Database Tool BioXpress is a gene expression and cancer association database in which the expression levels are mapped to genes using RNA-seq data obtained from The Cancer Genome Atlas, International Cancer Genome Consortium, Expression Atlas and publications. The BioXpress database includes expression data from 64 cancer types, 6361 patients and 17 469 genes with 9513 of the genes displaying differential expression between tumor and normal samples. In addition to data directly retrieved from RNA-seq data repositories, manual biocuration of publications supplements the available cancer association annotations in the database. All cancer types are mapped to Disease Ontology terms to facilitate a uniform pan-cancer analysis. The BioXpress database is easily searched using HUGO Gene Nomenclature Committee gene symbol, UniProtKB/RefSeq accession or, alternatively, can be queried by cancer type with specified significance filters. This interface along with availability of pre-computed downloadable files containing differentially expressed genes in multiple cancers enables straightforward retrieval and display of a broad set of cancer-related genes. Database URL: http://hive.biochemistry.gwu.edu/tools/bioxpress Oxford University Press 2015-03-28 /pmc/articles/PMC4377087/ /pubmed/25819073 http://dx.doi.org/10.1093/database/bav019 Text en © The Author(s) 2015. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://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 Tool Wan, Quan Dingerdissen, Hayley Fan, Yu Gulzar, Naila Pan, Yang Wu, Tsung-Jung Yan, Cheng Zhang, Haichen Mazumder, Raja BioXpress: an integrated RNA-seq-derived gene expression database for pan-cancer analysis |
title | BioXpress: an integrated RNA-seq-derived gene expression database for pan-cancer analysis |
title_full | BioXpress: an integrated RNA-seq-derived gene expression database for pan-cancer analysis |
title_fullStr | BioXpress: an integrated RNA-seq-derived gene expression database for pan-cancer analysis |
title_full_unstemmed | BioXpress: an integrated RNA-seq-derived gene expression database for pan-cancer analysis |
title_short | BioXpress: an integrated RNA-seq-derived gene expression database for pan-cancer analysis |
title_sort | bioxpress: an integrated rna-seq-derived gene expression database for pan-cancer analysis |
topic | Database Tool |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4377087/ https://www.ncbi.nlm.nih.gov/pubmed/25819073 http://dx.doi.org/10.1093/database/bav019 |
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