An inductive graph neural network model for compound–protein interaction prediction based on a homogeneous graph

Identifying the potential compound–protein interactions (CPIs) plays an essential role in drug development. The computational approaches for CPI prediction can reduce time and costs of experimental methods and have benefited from the continuously improved graph representation learning. However, most...

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Detalles Bibliográficos
Autores principales: Wan, Xiaozhe, Wu, Xiaolong, Wang, Dingyan, Tan, Xiaoqin, Liu, Xiaohong, Fu, Zunyun, Jiang, Hualiang, Zheng, Mingyue, Li, Xutong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Problem Solving Protocol
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9310259/
https://www.ncbi.nlm.nih.gov/pubmed/35275993
http://dx.doi.org/10.1093/bib/bbac073

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9310259/
https://www.ncbi.nlm.nih.gov/pubmed/35275993
http://dx.doi.org/10.1093/bib/bbac073

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