Cargando…
Machine Learning Prediction of Cancer Cell Sensitivity to Drugs Based on Genomic and Chemical Properties
Predicting the response of a specific cancer to a therapy is a major goal in modern oncology that should ultimately lead to a personalised treatment. High-throughput screenings of potentially active compounds against a panel of genomically heterogeneous cancer cell lines have unveiled multiple relat...
Autores principales: | Menden, Michael P., Iorio, Francesco, Garnett, Mathew, McDermott, Ultan, Benes, Cyril H., Ballester, Pedro J., Saez-Rodriguez, Julio |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3640019/ https://www.ncbi.nlm.nih.gov/pubmed/23646105 http://dx.doi.org/10.1371/journal.pone.0061318 |
Ejemplares similares
-
The germline genetic component of drug sensitivity in cancer cell lines
por: Menden, Michael P., et al.
Publicado: (2018) -
The evolving role of cancer cell line-based screens to define the impact of cancer genomes on drug response()
por: Garnett, Mathew J, et al.
Publicado: (2014) -
GDSCTools for mining pharmacogenomic interactions in cancer
por: Cokelaer, Thomas, et al.
Publicado: (2018) -
Pathway-based dissection of the genomic heterogeneity of cancer hallmarks’ acquisition with SLAPenrich
por: Iorio, Francesco, et al.
Publicado: (2018) -
Functional linkage of gene fusions to cancer cell fitness assessed by pharmacological and CRISPR-Cas9 screening
por: Picco, Gabriele, et al.
Publicado: (2019)