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An end-to-end deep learning architecture for extracting protein–protein interactions affected by genetic mutations

The BioCreative VI Track IV (mining protein interactions and mutations for precision medicine) challenge was organized in 2017 with the goal of applying biomedical text mining methods to support advancements in precision medicine approaches. As part of the challenge, a new dataset was introduced for...

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Dades bibliogràfiques
Publicat a:Database (Oxford)
Autors principals: Tran, Tung, Kavuluru, Ramakanth
Format: Artigo
Idioma:Inglês
Publicat: Oxford University Press 2018
Matèries:
Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC6146129/
https://ncbi.nlm.nih.gov/pubmed/30239680
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/database/bay092
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