Publication
SETH detects and normalizes genetic variants in text
Philippe Thomas; Tim Rocktäschel; Jörg Hakenberg; Yvonne Lichtblau; Ulf Leser
In: Bioinformatics, Vol. 32, No. 18, Pages 2883-2885, Oxford University Press, 2016.
Abstract
Summary: 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 http://rockt.github.io/SETH/.Contact: thomas@informatik.hu-berlin.de or leser@informatik.hu-berlin.de