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Database Commons - BioXpress

BioXpress

Citations: 5

z-index 0.33

Short name BioXpress
Full name
Description BioXpress is an integrated RNA-seq-derived gene expression database for pan-cancer analysis.
URL https://hive.biochemistry.gwu.edu/tools/bioxpress/
Year founded 2015
Last update & version NA    V 1.0
Availability Free to all users
University/Institution hosted The George Washington University
Address Washington,DC 20037,USA
City Washington
Province/State DC
Country/Region United States
Contact name Raja Mazumder
Contact email mazumder@gwu.edu
Data type(s)
Major organism(s)
Keyword(s)
  • cancer
Publication(s)
  • BioXpress: an integrated RNA-seq-derived gene expression database for pan-cancer analysis. [PMID: 25819073]

    Quan Wan, Hayley Dingerdissen, Yu Fan, Naila Gulzar, Yang Pan, Tsung-Jung Wu, Cheng Yan, Haichen Zhang, Raja Mazumder
    Database : the journal of biological databases and curation 2015:2015
    5 Citations (Google Scholar as of 2015-12-28)

    Abstract: 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. © The Author(s) 2015. Published by Oxford University Press.

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Tags

Disease DNA Expression
Homo sapiens
cancer

Record metadata

  • Created on: 2015-06-20
  • Curated by:
    • Mengwei Li [2016-03-29]
    • Mengwei Li [2015-11-29]
    • Mengwei Li [2015-06-26]
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