title: PPI-IRO: a two-stage method for protein-protein interaction extraction based on interaction relation ontology.
abstract: Mining Protein-Protein Interactions (PPIs) from the fast-growing biomedical literature resources has been proven as an effective approach for the identification of biological regulatory networks. This paper presents a novel method based on the idea of Interaction Relation Ontology (IRO), which specifies and organises words of various proteins interaction relationships. Our method is a two-stage PPI extraction method. At first, IRO is applied in a binary classifier 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 significant performance of IRO on relation sentences classification 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.
authors.forename: Chuan-Xi
authors.initials: CX
authors.lastname: Li
authors.forename: Peng
authors.initials: P
authors.lastname: Chen
authors.forename: Ru-Jing
authors.initials: RJ
authors.lastname: Wang
authors.forename: Xiu-Jie
authors.initials: XJ
authors.lastname: Wang
authors.forename: Ya-Ru
authors.initials: YR
authors.lastname: Su
authors.forename: Jinyan
authors.initials: J
authors.lastname: Li
mesh_terms: D000465:Algorithms; D019540:Area Under Curve; D001185:Artificial Intelligence; D019295:Computational Biology / Q000379:methods*; D003201:Computers; D057225:Data Mining; D011381:Programming Languages; D025941:Protein Interaction Mapping / Q000379:methods*; D015203:Reproducibility of Results; D012984:Software