GCRNN: graph convolutional recurrent neural network for compound–protein interaction prediction

BACKGROUND: Compound–protein interaction prediction is necessary to investigate health regulatory functions and promotes drug discovery. Machine learning is becoming increasingly important in bioinformatics for applications such as analyzing protein-related data to achieve successful solutions. Mode...

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Detalles Bibliográficos
Autores principales: Elbasani, Ermal, Njimbouom, Soualihou Ngnamsie, Oh, Tae-Jin, Kim, Eung-Hee, Lee, Hyun, Kim, Jeong-Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8753816/
https://www.ncbi.nlm.nih.gov/pubmed/35016607
http://dx.doi.org/10.1186/s12859-022-04560-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8753816/
https://www.ncbi.nlm.nih.gov/pubmed/35016607
http://dx.doi.org/10.1186/s12859-022-04560-x

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