Wan Quan, Dingerdissen Hayley, Fan Yu, Gulzar Naila, Pan Yang, Wu Tsung-Jung, Yan Cheng, Zhang Haichen, Mazumder Raja
Department of Biochemistry and Molecular Medicine and McCormick Genomic and Proteomic Center, The George Washington University, Washington, DC 20037, USA.
Department of Biochemistry and Molecular Medicine and McCormick Genomic and Proteomic Center, The George Washington University, Washington, DC 20037, USA Department of Biochemistry and Molecular Medicine and McCormick Genomic and Proteomic Center, The George Washington University, Washington, DC 20037, USA
Database (Oxford). 2015 Mar 28;2015. doi: 10.1093/database/bav019. Print 2015.
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.
BioXpress是一个基因表达与癌症关联数据库,其中利用从癌症基因组图谱、国际癌症基因组联盟、表达图谱和出版物中获得的RNA测序数据,将表达水平映射到基因上。BioXpress数据库包含来自64种癌症类型、6361名患者和17469个基因的表达数据,其中9513个基因在肿瘤样本和正常样本之间表现出差异表达。除了直接从RNA测序数据存储库中检索的数据外,对出版物的人工生物编目补充了数据库中可用的癌症关联注释。所有癌症类型都映射到疾病本体术语,以促进统一的泛癌分析。使用HUGO基因命名委员会基因符号、UniProtKB/RefSeq登录号可以轻松搜索BioXpress数据库,或者也可以通过癌症类型并使用指定的显著性筛选器进行查询。该界面以及包含多种癌症中差异表达基因的预计算可下载文件,使得能够直接检索和显示大量与癌症相关的基因。