BioPPIExtractor: A protein-protein interaction extraction system for biomedical literature

被引：7

作者：

Yang, Zhihao ^{[1
]}

Lin, Hongfei ^{[1
]}

Wu, Baodong ^{[1
]}

机构：

[1] Dalian Univ Technol, Dept Comp Sci & Technol, Dalian 116023, Peoples R China

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2009年 / 36卷 / 02期

关键词：

Conditional Random Fields; Link grammar parsing; Interaction extraction; DIP; INFORMATION; TEXT; GENE;

D O I：

10.1016/j.eswa.2007.12.014

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Automatic extracting protein-protein interaction information from biomedical literature can help to build protein relation network, predict protein function and design new drugs. This paper presents a protein-protein interaction extraction system BioPPIExtractor for biomedical literature. This system applies Conditional Random Fields model to tag protein names in biomedical text, then uses a link grammar parser to identify the syntactic roles in sentences and at last extracts complete interactions by analyzing the matching contents of syntactic roles and their linguistically significant combinations. Experimental evaluations with two other state of the art extraction systems indicate that BioPPlExtractor system achieves better performance. (C) 2007 Elsevier Ltd. All rights reserved.

引用

页码：2228 / 2233

页数：6

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