kGCN: a graph-based deep learning framework for chemical structures

Deep learning is developing as an important technology to perform various tasks in cheminformatics. In particular, graph convolutional neural networks (GCNs) have been reported to perform well in many types of prediction tasks related to molecules. Although GCN exhibits considerable potential in var...

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Detalles Bibliográficos
Autores principales: Kojima, Ryosuke, Ishida, Shoichi, Ohta, Masateru, Iwata, Hiroaki, Honma, Teruki, Okuno, Yasushi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2020
Materias:
Software
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7216578/
https://www.ncbi.nlm.nih.gov/pubmed/33430993
http://dx.doi.org/10.1186/s13321-020-00435-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7216578/
https://www.ncbi.nlm.nih.gov/pubmed/33430993
http://dx.doi.org/10.1186/s13321-020-00435-6

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