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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Detalles Bibliográficos
Autores principales: Rinaldi, Fabio, Ellendorff, Tilia Renate, Madan, Sumit, Clematide, Simon, van der Lek, Adrian, Mevissen, Theo, Fluck, Juliane
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4940434/
https://www.ncbi.nlm.nih.gov/pubmed/27402677
http://dx.doi.org/10.1093/database/baw067

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4940434/
https://www.ncbi.nlm.nih.gov/pubmed/27402677
http://dx.doi.org/10.1093/database/baw067

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