Predicting responses to platin chemotherapy agents with biochemically-inspired machine learning

The selection of effective genes that accurately predict chemotherapy responses might improve cancer outcomes. We compare optimized gene signatures for cisplatin, carboplatin, and oxaliplatin responses in the same cell lines and validate each signature using data from patients with cancer. Supervise...

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Detalles Bibliográficos
Autores principales: Mucaki, Eliseos J., Zhao, Jonathan Z. L., Lizotte, Daniel J., Rogan, Peter K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6329797/
https://www.ncbi.nlm.nih.gov/pubmed/30652029
http://dx.doi.org/10.1038/s41392-018-0034-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6329797/
https://www.ncbi.nlm.nih.gov/pubmed/30652029
http://dx.doi.org/10.1038/s41392-018-0034-5

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