Inter-species normalization of gene mentions with GNAT
Inter-species normalization of gene mentions with GNAT
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DOI：
10.1093/bioinformatics/btn299
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发表时间：
2008-08-15
期刊：
影响因子：
5.8
通讯作者：
Gonzalez, Graciela
中科院分区：
文献类型：
--
作者：
Hakenberg, Joerg;Plake, Conrad;Gonzalez, Graciela
动机：生物医学领域的文本挖掘旨在帮助研究人员以更快、更容易和更完整的方式获取科学出版物中包含的信息。实现这一目标的一个步骤是识别命名实体，并随后将其归一化为数据库标识。标准化有助于将潜在感兴趣的对象，如基因，与出版物中未包含的详细信息联系起来；它也是整合不同知识来源的关键。从信息检索的角度来看，标准化促进了索引和查询。由于基因名称的高度多义性，基因提及标准化(GN)尤其具有挑战性：它们指的是同源或完全不同的基因，以表型和其他生物医学术语命名，或者它们类似于常见的英语单词。结果：我们提出了第一个公开可用的系统，GNAT，据报道可以处理物种间的GN。我们的方法使用广泛的基因背景知识来将含糊的名称解析为Entrezgene识别符。它的性能与我们和其他人提出的单物种方法相当。在一个从BioCreative 1和BioCreative 2数据中得出的基准集上，包含13个物种的基因，GNAT的F度量为81.4(在73.8次召回时的准确率为90.8)。对于单一物种的任务，我们报告了人类基因的F-度量为85.4。
Motivation: Text mining in the biomedical domain aims at helping researchers to access information contained in scientific publications in a faster, easier and more complete way. One step towards this aim is the recognition of named entities and their subsequent normalization to database identifiers. Normalization helps to link objects of potential interest, such as genes, to detailed information not contained in a publication; it is also key for integrating different knowledge sources. From an information retrieval perspective, normalization facilitates indexing and querying. Gene mention normalization (GN) is particularly challenging given the high ambiguity of gene names: they refer to orthologous or entirely different genes, are named after phenotypes and other biomedical terms, or they resemble common English words.Results: We present the first publicly available system, GNAT, reported to handle inter-species GN. Our method uses extensive background knowledge on genes to resolve ambiguous names to EntrezGene identifiers. It performs comparably to single-species approaches proposed by us and others. On a benchmark set derived from BioCreative 1 and 2 data that contains genes from 13 species, GNAT achieves an F-measure of 81.4 (90.8 precision at 73.8 recall). For the single-species task, we report an F-measure of 85.4 on human genes.