BEST: Next-Generation Biomedical Entity Search Tool for Knowledge Discovery from Biomedical Literature.
作者: Sunwon LeeDonghyeon KimKyubum LeeJaehoon ChoiSeongsoon KimMinji JeonSangrak LimDonghee ChoiSunkyu KimAik-Choon TanJaewoo Kang
刊名: PLoS ONE, 2017, Vol.11 (10)
来源数据库: Directory of Open Access Journals
DOI: 10.1371/journal.pone.0164680
原始语种摘要: As the volume of publications rapidly increases, searching for relevant information from the literature becomes more challenging. To complement standard search engines such as PubMed, it is desirable to have an advanced search tool that directly returns relevant biomedical entities such as targets, drugs, and mutations rather than a long list of articles. Some existing tools submit a query to PubMed and process retrieved abstracts to extract information at query time, resulting in a slow response time and limited coverage of only a fraction of the PubMed corpus. Other tools preprocess the PubMed corpus to speed up the response time; however, they are not constantly updated, and thus produce outdated results. Further, most existing tools cannot process sophisticated queries such as...
全文获取路径: DOAJ  (合作)
影响因子:3.73 (2012)

  • returns 返回粉末
  • information 报告
  • process 过程
  • relevant 有关联的
  • query 查询
  • outdated 过期的
  • BEST 电渣浇注
  • rapidly 迅速地
  • search 搜索
  • including 包括(气导)包括……在内包括…在内