PPI-IRO: A two-stage method for protein-protein interaction extraction based on interaction relation ontology

Publication Type:
Journal Article
Citation:
International Journal of Data Mining and Bioinformatics, 2014, 10 (1), pp. 98 - 119
Issue Date:
2014-01-01
Metrics:
Full metadata record
Files in This Item:
Filename Description Size
Thumbnailppi-iro.pdfPublished Version564.77 kB
Adobe PDF
Mining Protein-Protein Interactions (PPIs) from the fast-growing biomedical literature resources has been proven as an effective approach for the identifi cation of biological regulatory networks. This paper presents a novel method based on the idea of Interaction Relation Ontology (IRO), which specifi es and organises words of various proteins interaction relationships. Our method is a two-stage PPI extraction method. At fi rst, IRO is applied in a binary classifi er to determine whether sentences contain a relation or not. Then, IRO is taken to guide PPI extraction by building sentence dependency parse tree. Comprehensive and quantitative evaluations and detailed analyses are used to demonstrate the signifi cant performance of IRO on relation sentences classifi cation and PPI extraction. Our PPI extraction method yielded a recall of around 80% and 90% and an F1 of around 54% and 66% on corpora of AIMed and Bioinfer, respectively, which are superior to most existing extraction methods. Copyright © 2014 Inderscience Enterprises Ltd.
Please use this identifier to cite or link to this item: