Learning rules to extract protein interactions from biomedical text

Authors:
Tu Minh Phuong;Doheon Lee;Kwang Hyung Lee
Affiliations:
Department of BioSystems, KAIST, Daejeon, Korea;Department of BioSystems, KAIST, Daejeon, Korea;Department of BioSystems, KAIST, Daejeon, Korea
Venue:
PAKDD'03 Proceedings of the 7th Pacific-Asia conference on Advances in knowledge discovery and data mining
Year:
2003

Citing 4
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Abstract

We present a method for automatic extraction of protein interactions from scientific abstracts by combing machine learning and knowledge-based strategies. This method uses sample sentences, which are parsed by a link grammar parser, to learn extraction rules automatically. By incorporating heuristic rules based on morphological clues and domain specific knowledge, this method can remove the interactions that are not between proteins and improve the performance of extraction process. We present experimental results for a test set of MEDLINE abstracts. The results are encouraging and demonstrate the feasibility of our method to perform accurate extraction without need of manual rule building.