A Comparison of Methods for Data-Driven Cancer Outlier Discovery, and An Application Scheme to Semisupervised Predictive Biomarker Discovery

A core component in translational cancer research is biomarker discovery using gene expression profiling for clinical tumors. This is often based on cell line experiments; one population is sampled for inference in another. We disclose a semisupervised workflow focusing on binary (switch-like, bimod...

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Detalles Bibliográficos
Autores principales: Karrila, Seppo, Lee, Julian Hock Ean, Tucker-Kellogg, Greg
Formato: Texto
Lenguaje:English
Publicado: Libertas Academica 2011
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3091411/
https://www.ncbi.nlm.nih.gov/pubmed/21584264
http://dx.doi.org/10.4137/CIN.S6868

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3091411/
https://www.ncbi.nlm.nih.gov/pubmed/21584264
http://dx.doi.org/10.4137/CIN.S6868

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