Year : 2004 Mining relations in the GENIA corpus

Discovering the interactions between genes and proteins is seen as one of the core tasks in molecular biology. The quantity of research results in this area is growing at such arate that it is very dicult for individual researchers to keep track of them. As such results appear mainly in the form of scientic articles, it is necessary to process them in an ecient manner in order to be able to extract the relevant results. Many databases exist that aim at consolidating the newly gained knowledge in a format that is easily accessible and searchable, however the creators of such databases normally make use of human readers who manually curate the relevant papers. This is an expensive and time consuming process, besides, there might be a signicant time lag between the publication of a result and its introduction into such databases. In this paper we propose a method for discovery of interactions between genes and proteins from the scientic literature, based on a complete syntactic analysis of the corpus. We report on preliminary results. Posted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: https://doi.org/10.5167/uzh-19121 Originally published at: Rinaldi, Fabio; Schneider, G; Kaljurand, K; Dowdall, J; Andronis, C; Persidis, A; Konstanti, O (2004). Mining relations in the GENIA corpus. In: Second European Workshop on Data Mining and Text Mining for Bioinformatics, Pisa, Italy, September 2004 September 2004, 61-68. Mining relations in the GENIA corpus Fabio Rinaldi, Gerold Schneider, Kaarel Kaljurand , James Dowdall∗ Institute of Computational Linguistics, University of Zurich, CH-8057 Zürich, Switzerland http://www.cl.unizh.ch/ {rinaldi,gschneid,kalju,dowdall}@ifi.unizh.ch Christos Andronis, Andreas Persidis, Ourania Konstanti Biovista, 34 Rodopoleos Str, Ellinikon, GR-16777 Athens Greece http://www.biovista.com/ {candronis, andreasp, okonst}@biovista.com