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  • 标题:SIA: a scalable interoperable annotation server for biomedical named entities
  • 作者:Johannes Kirschnick ; Philippe Thomas ; Roland Roller
  • 期刊名称:Journal of Cheminformatics
  • 印刷版ISSN:1758-2946
  • 电子版ISSN:1758-2946
  • 出版年度:2018
  • 卷号:10
  • 期号:1
  • 页码:63
  • DOI:10.1186/s13321-018-0319-2
  • 语种:English
  • 出版社:BioMed Central
  • 摘要:Recent years showed a strong increase in biomedical sciences and an inherent increase in publication volume. Extraction of specific information from these sources requires highly sophisticated text mining and information extraction tools. However, the integration of freely available tools into customized workflows is often cumbersome and difficult. We describe SIA (Scalable Interoperable Annotation Server), our contribution to the BeCalm-Technical interoperability and performance of annotation servers (BeCalm-TIPS) task, a scalable, extensible, and robust annotation service. The system currently covers six named entity types (i.e., chemicals, diseases, genes, miRNA, mutations, and organisms) and is freely available under Apache 2.0 license at https://github.com/Erechtheus/sia .
  • 关键词:Text mining ; Annotation service ; Robustness ; Scalability ; Extensibility
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