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Track 4 overview: Extraction of causal network information in biological expression language (BEL)

: Fluck, Juliane; Madan, Sumit; Ellendorf, Tilia; Mevissen, Heinz-Theodor; Clematide, Simon; Lek, Adrian van der; Rinaldi, Fabio

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Fifth BioCreative Challenge Evaluation Workshop 2015. Proceedings. Online resource : Sevilla, Spain, 9-11 September 2015
Sevilla, 2015
BioCreative Challenge Evaluation Workshop <5, 2015, Sevilla>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer SCAI ()

Automatic extraction of biological network information is one of the most desired and most complex tasks in biological text mining. The BioCreative track 4 provides training data and an evaluation environment for the extraction of causal relationships in Biological Expression Language (BEL). BEL is a modeling language that is easily editable by humans or by automatic systems and can express causal relationships of different levels of granularity. Proteinprotein relations can be expressed in BEL as well as relations between biological processes and disease stages. To extract BEL information automatically, named entity recognition and normalization to defined name spaces are necessary. Furthermore, relations extracted from text have to be transformed into correct BEL syntax. The track provided training and evaluation for two complementary task: Given a sentence extract all BEL statements and given a BEL statement propose up to 10 evidence sentences from the literature.