WebGIVI: a web-based gene enrichment analysis and visualization tool
作者: Liang SunYongnan ZhuA. S. M. Ashique MahmoodCatalina O. TudorJia RenK. Vijay-ShankerJian ChenCarl J. Schmidt
作者单位: 1University of Delaware
2Current address: Computing Service, The Samuel Roberts Noble Foundation
3University of Maryland Baltimore County
4Hangzhou Dianzi University
刊名: BMC Bioinformatics, 2017, Vol.18 (1)
来源数据库: Springer Nature Journal
DOI: 10.1186/s12859-017-1664-2
关键词: VisualizationEGIFTGene iTermGene enrichmentWeb development
原始语种摘要: A major challenge of high throughput transcriptome studies is presenting the data to researchers in an interpretable format. In many cases, the outputs of such studies are gene lists which are then examined for enriched biological concepts. One approach to help the researcher interpret large gene datasets is to associate genes and informative terms (iTerm) that are obtained from the biomedical literature using the eGIFT text-mining system. However, examining large lists of iTerm and gene pairs is a daunting task.
全文获取路径: Springer Nature  (合作)
影响因子:3.024 (2012)

  • enrichment 富集
  • visualization 目测
  • informative 丰富的资料
  • mining 矿业
  • large 大的
  • associate 使联合
  • lists 广义表
  • interpret 说明
  • development 开发
  • researcher 研究员