| Literature DB >> 20671319 |
Fabio Rinaldi1, Gerold Schneider, Kaarel Kaljurand, Simon Clematide, Thérèse Vachon, Martin Romacker.
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.Mesh:
Year: 2010 PMID: 20671319 DOI: 10.1109/TCBB.2010.50
Source DB: PubMed Journal: IEEE/ACM Trans Comput Biol Bioinform ISSN: 1545-5963 Impact factor: 3.710