OntoGene in BioCreative II.5

Authors:
Fabio Rinaldi;Gerold Schneider;Kaarel Kaljurand;Simon Clematide;Thérèse Vachon;Martin Romacker
Affiliations:
University of Zurich;University of Zurich, Zurich;University of Zurich, Zurich;University of Zurich, Zurich;Novartis Pharma AG, NITAS, Text Mining Services, Basel;Novartis Pharma AG, NITAS, Text Mining Services, Basel
Venue:
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Year:
2010

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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.