SETH detects and normalizes genetic variants in text

被引：22

作者：

Thomas, Philippe ^{[1
,2
]}

Rocktaschel, Tim ^{[3
]}

Hakenberg, Jorg ^{[4
]}

Lichtblau, Yvonne ^{[2
]}

Leser, Ulf ^{[2
]}

机构：

[1] DFKI Berlin, Language Technol Lab, Berlin, Germany

[2] Humboldt Univ, Inst Comp Sci, Knowledge Management Bioinformat, Unter Linden 6, D-10099 Berlin, Germany

[3] UCL, Gower St, London WC1E 6BT, England

[4] Illumina Inc, 451 El Camino Real, Santa Clara, CA 95050 USA

来源：

BIOINFORMATICS | 2016年 / 32卷 / 18期

关键词：

BIOMEDICAL LITERATURE; SEQUENCE VARIANTS; MUTATIONS; NOMENCLATURE; CANCER; SYSTEM;

D O I：

10.1093/bioinformatics/btw234

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

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.

引用

收藏

页码：2883 / 2885

页数：3

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