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Mining relations in the GENIA corpus


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.

Abstract

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 rel-
evant papers. This is an expensive and time consuming
process, besides, there might be a signicant time lag be-
tween the publication of a result and its introduction into
such databases.
In this paper we propose a method for discovery of inter-
actions between genes and proteins from the scientic liter-
ature, based on a complete syntactic analysis of the corpus.
We report on preliminary results.

Abstract

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 rel-
evant papers. This is an expensive and time consuming
process, besides, there might be a signicant time lag be-
tween the publication of a result and its introduction into
such databases.
In this paper we propose a method for discovery of inter-
actions between genes and proteins from the scientic liter-
ature, based on a complete syntactic analysis of the corpus.
We report on preliminary results.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Language:English
Event End Date:September 2004
Deposited On:06 Aug 2009 11:57
Last Modified:22 Aug 2017 21:10

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