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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...
| Autores principales: | , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
Libertas Academica
2011
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| 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 |