BioCreative V track 4: a shared task for the extraction of causal network information using the Biological Expression Language

Automatic extraction of biological network information is one of the most desired and most complex tasks in biological and medical text mining. Track 4 at BioCreative V attempts to approach this complexity using fragments of large-scale manually curated biological networks, represented in Biological...

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Библиографические подробности
Опубликовано в: :Database (Oxford)
Главные авторы: Rinaldi, Fabio, Ellendorff, Tilia Renate, Madan, Sumit, Clematide, Simon, van der Lek, Adrian, Mevissen, Theo, Fluck, Juliane
Формат: Artigo
Язык:Inglês
Опубликовано: Oxford University Press 2016
Предметы:
Original Article
Online-ссылка:https://ncbi.nlm.nih.gov/pmc/articles/PMC4940434/
https://ncbi.nlm.nih.gov/pubmed/27402677
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/database/baw067
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