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  4. Automatic extraction of BEL-statements based on neural networks
 
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2017
Conference Paper
Titel

Automatic extraction of BEL-statements based on neural networks

Abstract
The automatic extraction of biomedical relations and entities from text has become extremely important in systems biology. For coding the extracted information, the Biological Expression Language (BEL) can be used. A BEL-statement consists of a subject (entity), a predicate (type of relationship), and an object (entity or a further BEL-statement). This paper describes a system based on neural networks (NNs) to extract BEL-statements in the context of the BioCreAtivE 2017 track 3 (task 1) challenge. In our approach, the overall problem is divided into four subtasks: (i) the detection of named entities (NER), (ii) deciding whether a pair of entities participate in a relation, (iii) determining which of the entities participating in a relation is the subject/object entity, and (iv) extracting the type of the relation. By merging the solutions of the subtasks, the BEL-statements are generated. Except for the named entity recognition, (convolutional) NNs were used to solve the tasks. The results show that a neural net based approach is reasonable to use for the extraction of biomedical relations. The limitations of our system are related to the small size (compared to other NN-based applications) of the data set. We argue that by overcoming this limitation, promising results can be expected from NN-based approaches in future.
Author(s)
Ali, Mehdi
University of Bonn, 53012 Bonn
Madan, Sumit
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI
Fischer, Asja
University of Bonn, 53012 Bonn
Petzka, Henning
University of Bonn, 53012 Bonn
Fluck, Juliane
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI
Hauptwerk
BioCreative VI Workshop 2017. Proceedings. Online resource (Nicht mehr online verfügbar)
Konferenz
BioCreative Challenge Evaluation Workshop 2017
DOI
10.24406/publica-fhg-400728
File(s)
N-497297.pdf (2.33 MB)
Language
English
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Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI
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