Random Subspace Aggregation for Cancer Prediction with Gene Expression Profiles.
Background. Precisely predicting cancer is crucial for cancer treatment. Gene expression profiles make it possible to analyze patterns between genes and cancers on the genome-wide scale. Gene expression data analysis, however, is confronted with enormous challenges for its characteristics, such as h...
| Publicado en: | BioMed Research International Vol. 2016; pp. 1 - 11 |
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| Autores principales: | , , , , |
| Formato: | algorithm research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
11/24/2016
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| Acceso en línea: | Ver este registro en EBSCOhost |