Predicting Biomedical Interactions with Higher-Order Graph Convolutional Networks

Biomedical interaction networks have incredible potential to be useful in the prediction of biologically meaningful interactions, identification of network biomarkers of disease, and the discovery of putative drug targets. Recently, graph neural networks have been proposed to effectively learn repre...

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Detalles Bibliográficos
Autores principales: KC, Kishan, Li, Rui, Cui, Feng, Haake, Anne R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8518029/
https://www.ncbi.nlm.nih.gov/pubmed/33587705
http://dx.doi.org/10.1109/TCBB.2021.3059415

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8518029/
https://www.ncbi.nlm.nih.gov/pubmed/33587705
http://dx.doi.org/10.1109/TCBB.2021.3059415

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