Drug response prediction using graph representation learning and Laplacian feature selection

BACKGROUND: Knowing the responses of a patient to drugs is essential to make personalized medicine practical. Since the current clinical drug response experiments are time-consuming and expensive, utilizing human genomic information and drug molecular characteristics to predict drug responses is of...

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Detalles Bibliográficos
Autores principales: Xie, Minzhu, Lei, Xiaowen, Zhong, Jianchen, Ouyang, Jianxing, Li, Guijing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Methodology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9733001/
https://www.ncbi.nlm.nih.gov/pubmed/36494630
http://dx.doi.org/10.1186/s12859-022-05080-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9733001/
https://www.ncbi.nlm.nih.gov/pubmed/36494630
http://dx.doi.org/10.1186/s12859-022-05080-4

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