A graph neural network approach for molecule carcinogenicity prediction

MOTIVATION: Molecular carcinogenicity is a preventable cause of cancer, but systematically identifying carcinogenic compounds, which involves performing experiments on animal models, is expensive, time consuming and low throughput. As a result, carcinogenicity information is limited and building dat...

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Detalles Bibliográficos
Autores principales: Fradkin, Philip, Young, Adamo, Atanackovic, Lazar, Frey, Brendan, Lee, Leo J, Wang, Bo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
ISCB/Ismb 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9235510/
https://www.ncbi.nlm.nih.gov/pubmed/35758812
http://dx.doi.org/10.1093/bioinformatics/btac266

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9235510/
https://www.ncbi.nlm.nih.gov/pubmed/35758812
http://dx.doi.org/10.1093/bioinformatics/btac266

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