SETH detects and normalizes genetic variants in text

Bioinformatics. 2016 Sep 15;32(18):2883-5. doi: 10.1093/bioinformatics/btw234. Epub 2016 Jun 2.


: Descriptions of genetic variations and their effect are widely spread across the biomedical literature. However, finding all mentions of a specific variation, or all mentions of variations in a specific gene, is difficult to achieve due to the many ways such variations are described. Here, we describe SETH, a tool for the recognition of variations from text and their subsequent normalization to dbSNP or UniProt. SETH achieves high precision and recall on several evaluation corpora of PubMed abstracts. It is freely available and encompasses stand-alone scripts for isolated application and evaluation as well as a thorough documentation for integration into other applications.

Availability and implementation: SETH is released under the Apache 2.0 license and can be downloaded from CONTACT: or

MeSH terms

  • Computational Biology / methods
  • Data Curation*
  • Data Mining*
  • Genes
  • Genetic Variation*
  • Humans
  • Information Storage and Retrieval / methods
  • Natural Language Processing
  • PubMed
  • Publications
  • Terminology as Topic