Tagging gene and protein names in biomedical text

被引：166

作者：

Tanabe, L ^{[1
]}

Wilbur, WJ ^{[1
]}

机构：

[1] Natl Lib Med, Natl Ctr Biotechnol Informat, NIH, Bethesda, MD 20894 USA

来源：

BIOINFORMATICS | 2002年 / 18卷 / 08期

关键词：

D O I：

10.1093/bioinformatics/18.8.1124

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Motivation: The MEDLINE database of biomedical abstracts contains scientific knowledge about thousands of interacting genes and proteins. Automated text processing can aid in the comprehension and synthesis of this valuable information. The fundamental task of identifying gene and protein names is a necessary first step towards making full use of the information encoded in biomedical text. This remains a challenging task due to the irregularities and ambiguities in gene and protein nomenclature. We propose to approach the detection of gene and protein names in scientific abstracts as part-of-speech tagging, the most basic form of linguistic corpus annotation. Results: We present a method for tagging gene and protein names in biomedical text using a combination of statistical and knowledge-based strategies. This method incorporates automatically generated rules from a transformation-based part-of-speech tagger, and manually generated rules from morphological clues, low frequency trigrams, indicator terms, suffixes and part-of-speech information. Results of an experiment on a test corpus of 56K MEDLINE documents demonstrate that our method to extract gene and protein names can be applied to large sets of MEDLINE abstracts, without the need for special conditions or human experts to predetermine relevant subsets.

引用

页码：1124 / 1132

页数：9

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