Deep-learning: investigating deep neural networks hyper-parameters and comparison of performance to shallow methods for modeling bioactivity data

BACKGROUND: In recent years, research in artificial neural networks has resurged, now under the deep-learning umbrella, and grown extremely popular. Recently reported success of DL techniques in crowd-sourced QSAR and predictive toxicology competitions has showcased these methods as powerful tools i...

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Detalles Bibliográficos
Autores principales: Koutsoukas, Alexios, Monaghan, Keith J., Li, Xiaoli, Huan, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5489441/
https://www.ncbi.nlm.nih.gov/pubmed/29086090
http://dx.doi.org/10.1186/s13321-017-0226-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5489441/
https://www.ncbi.nlm.nih.gov/pubmed/29086090
http://dx.doi.org/10.1186/s13321-017-0226-y

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