Title of article
BioPPIExtractor: A protein–protein interaction extraction system for biomedical literature
Author/Authors
Yang، نويسنده , , Zhihao and Lin، نويسنده , , Hongfei and Wu، نويسنده , , Baodong، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2009
Pages
6
From page
2228
To page
2233
Abstract
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 BioPPIExtractor system achieves better performance.
Keywords
Interaction extraction , Link grammar parsing , DIP , conditional random fields
Journal title
Expert Systems with Applications
Serial Year
2009
Journal title
Expert Systems with Applications
Record number
2345298
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