OntoGene in BioCreative II.5.
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.
Rinaldi
Fabio
F
Institute of Computational Linguistics, University of Zurich, Zurich, Switzerland. rinaldi@cl.uzh.ch
Schneider
Gerold
G
Kaljurand
Kaarel
K
Clematide
Simon
S
Vachon
Thérèse
T
Romacker
Martin
M
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