title: OntoGene in BioCreative II.5.
abstract: We describe a system for the detection of mentions of protein-protein interactions in the biomedical scientific literature. The original system was developed as a part of the OntoGene project, which focuses on using advanced computational linguistic techniques for text mining applications in the biomedical domain. In this paper, we focus in particular on the participation to the BioCreative II.5 challenge, where the OntoGene system achieved best-ranked results. Additionally, we describe a feature-analysis experiment performed after the challenge, which shows the unexpected result that one single feature alone performs better than the combination of features used in the challenge.
authors.affiliation: Institute of Computational Linguistics, University of Zurich, Zurich, Switzerland. rinaldi@cl.uzh.ch
authors.forename: Fabio
authors.initials: F
authors.lastname: Rinaldi
authors.forename: Gerold
authors.initials: G
authors.lastname: Schneider
authors.forename: Kaarel
authors.initials: K
authors.lastname: Kaljurand
authors.forename: Simon
authors.initials: S
authors.lastname: Clematide
authors.forename: Thérèse
authors.initials: T
authors.lastname: Vachon
authors.forename: Martin
authors.initials: M
authors.lastname: Romacker
mesh_terms: D019295:Computational Biology / Q000379:methods*; D057225:Data Mining / Q000379:methods*; D016206:Databases, Bibliographic; D009323:Natural Language Processing; D025941:Protein Interaction Mapping / Q000379:methods*; D012958:Societies, Scientific