Knowledge-based gene symbol disambiguation

He Tan
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引用次数: 5

Abstract

Since there is no standard naming convention for genes and gene products, gene symbol disambiguation (GSD) has become a big challenge when mining biomedical literature. Several GSD methods have been proposed based on MEDLINE references to genes. However, nowadays gene databases, e.g. Entrez Gene, provide plenty of information about genes, and many biomedical ontologies, e.g. UMLS Metathesaurus and Semantic Network, have been developed. These knowledge sources could be used for disambiguation, in this paper we propose a method which relies on information about gene candidates from gene databases, contexts of gene symbols and biomedical ontologies. We implement our method, and evaluate the performance of the implementation using BioCreAtIvE II data sets.
基于知识的基因符号消歧
由于基因和基因产物没有统一的命名规范,基因符号消歧(GSD)成为生物医学文献挖掘的一大难题。已经提出了几种基于MEDLINE基因参考的GSD方法。目前,基因数据库如Entrez gene提供了大量的基因信息,生物医学本体如UMLS meta - thesaurus和Semantic Network也得到了发展。本文提出了一种基于基因数据库、基因符号上下文和生物医学本体的候选基因信息消歧方法。我们实现了我们的方法,并使用BioCreAtIvE II数据集评估了实现的性能。
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