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
Link To Document :
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