Gene Selection using a High-Dimensional Regression Model with Microarrays in Cancer Prognostic Studies
Mining of gene expression data to identify genes associated with patient survival is an ongoing problem in cancer prognostic studies using microarrays in order to use such genes to achieve more accurate prognoses. The least absolute shrinkage and selection operator (lasso) is often used for gene sel...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2012-01-01
|
| Series: | Cancer Informatics |
| Online Access: | https://doi.org/10.4137/CIN.S9048 |