Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas

Precision oncology uses genomic evidence to match patients with treatment but often fails to identify all patients who may respond. The transcriptome of these “hidden responders” may reveal responsive molecular states. We describe and evaluate a machine-learning approach to classify aberrant pathway...

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Detalles Bibliográficos
Autores principales: Way, Gregory P., Sanchez-Vega, Francisco, La, Konnor, Armenia, Joshua, Chatila, Walid K., Luna, Augustin, Sander, Chris, Cherniack, Andrew D., Mina, Marco, Ciriello, Giovanni, Schultz, Nikolaus, Sanchez, Yolanda, Greene, Casey S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5918694/
https://www.ncbi.nlm.nih.gov/pubmed/29617658
http://dx.doi.org/10.1016/j.celrep.2018.03.046

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5918694/
https://www.ncbi.nlm.nih.gov/pubmed/29617658
http://dx.doi.org/10.1016/j.celrep.2018.03.046

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