SYNPRED: prediction of drug combination effects in cancer using different synergy metrics and ensemble learning

BACKGROUND: In cancer research, high-throughput screening technologies produce large amounts of multiomics data from different populations and cell types. However, analysis of such data encounters difficulties due to disease heterogeneity, further exacerbated by human biological complexity and genom...

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Detalles Bibliográficos
Autores principales: Preto, António J, Matos-Filipe, Pedro, Mourão, Joana, Moreira, Irina S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Technical Note
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9511701/
https://www.ncbi.nlm.nih.gov/pubmed/36155782
http://dx.doi.org/10.1093/gigascience/giac087

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9511701/
https://www.ncbi.nlm.nih.gov/pubmed/36155782
http://dx.doi.org/10.1093/gigascience/giac087

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